- Email: [email protected]
A computer program designed to compare the spatial elements of handwriting
Forensic Science International
Forensic Science International 68 (1994) 195-203
A computer program designed to compare spatial elements of handwriting Doug Rogers,
Bryan Found*, Department
OJ Human Biosciences,
Robert
the
Schmittat
La Trobe University. 607 Swanston Street, Auslralia 3053
Carlton South,
Victoria,
Received 20 April 1994; accepted 2 June 1994
Abstract The comparison of questioned and standard line traces in forensic handwriting examination has to date been based almost entirely on subjective techniques. Handwriting examiners have not been equipped with a basic user-friendly technique to perform measurements on what are non-linear and variable behavioural artifacts. This paper describes a technique developed through research into human motor control which has been modified to be used by forensic handwriting examiners. The program provides a series of measurement tools. These tools can be applied to scanned images for the purpose of determining the spatial consistency of a disputed sample with a body of known writings. It is thought that the immediate application for this technique in the forensic casework environment is for the comparison of disputed signatures. In addition, the program can be used for any forensic research project requiring objective spatial data. If the field of forensic handwriting examination is to be considered a scientific endeavour, then the move toward the inclusion of objective measurement as part of the overall comparison methodology must be made. Keywords:
Image
processing;
Objective
analysis;
Spatial
data;
Signatures;
Document
examination
1. Introduction The field of routine almost
total
absence
of a questioned
forensic
handwriting
of objective
data
image
in comparison
comparison
has always
to aid in the determination to a group
of known
writings.
* Corresponding author 0379-0738/94/$07.00 0 1994 Elsevier Science Ireland SSDI
0379-0738(94)01558-M
suffered
Ltd. All rights reserved
from an
of the consistency Hilton
clearly
196
B. Found et al. /Forensic
Sci. ht. 68 (1994)
195-203
states “We are concerned in every signature problem with whether the specimen before us is consistent with the variable group of signatures that the person is capable of producing or normally uses to represent himself or herself’ [ 11. Opinions as to consistency should maximise the use of objective comparison techniques. It is well known that handwriting measurement has been employed by researchers in signature verification techniques and database searching strategies. The thrust of this paper is, however, toward a measurement tool that can be applied to routine signature comparisons. Of particular relevance is the work conducted on the statistical analysis of handwriting features and their variations [2-41. In a scientific sense, objective techniques can offer a powerful input into any examination. Objective techniques will provide numerical answers to questions as to whether a particular spatial element falls within the variation of a group of known material. Instrumental techniques facilitate reproducibility of results, given the same material. Data of this type can be used to develop criteria on which levels of opinion can be expressed. Criteria can be developed which provide indicators of the complexity of signatures, which is related to the degree of difficulty associated with copying a given image. Clearly the potential for objective techniques in routine casework and developmental research is enormous. The importance of this type of approach is well summarised in the following passage: If we have any hope of achieving accuracy and precision in examination results, any wish to serve the judicial system as we should, any aspiration to acquire the mantle of science, we must embark on the pursuit of measurement in handwriting identification. [5]
The software described in this report was designed for the purpose of providing a technique that could make objective measurements from two-dimensional static images, taking into account the path that the image was formed in. Handwriting generates such images. Spatial measurements of the artifact has always been difficult by virtue of the non-linear nature of many of the parameters required to be measured and the tendency for the path of one section of the line to overlap with previously formed sections. Simple pixel counting software produces errors related to the overlapping sections and associated with the relative alignment of screen pixels. The software we have developed for forensic applications we have called the Pattern Evidence Analysis Toolbox (PEAT). The PEAT software is a user-friendly package providing tools which enable handwriting examiners to accurately measure the total line length, the total area enclosed by the line, the area of any enclosed region, the path length between any two points, the straight line distance between any two points and angles directly from scanned images. It is structured in a normal standard image to questioned image comparison format. The results of any comparison will provide the examiner with a clear profile of what spatial features fall within or outside of the variation of the given body of standard material. 2. Equipment The PEAT as it is being currently
used requires
hardware
in the form of an Apple
B. Found et al. /Forensic
Sci. ht. 68 (1994)
197
195-203
Macintosh computer (series II or above) and an Apple One Scanner (300 d.p.i or greater). The software requirements are the PEAT, an image processing package (Image 1.41) and a spreadsheet package (ClarisWorks). 3. Method 3.1. Image preparation Images requiring analysis are enlarged on a photocopier so as to approximately tit across an A4 sheet of paper. A calibration grid accompanies each image through the enlargement process. The enlarged images are then scanned into a computer and saved as a PICT file. Once all images have been scanned they are processed using Image 1.41 software. A routine such as density slicing is carried out on the image to set upper and lower grey scale limits that will result in the image appearing as a complete and continuous line. Under normal circumstances, a simple threshold routine will accomplish this. Images are then converted to a binary form by setting the image pixels to black and all other pixels to white. A skeletonisation routine is applied which reduces the lines in the image to a thickness of one pixel. The processed images are saved in a MacPaint format. 3.2. The PEAT technique The overall structure of the PEAT technique is represented in Fig. 1. The format is based on a typical questioned to standard forensic comparison.-The program is
\ f PARAMETERISATION I
ANALYSIS-
( Fig. 1. Structure
of the PEAT program.
RESULTS
1
198
B. Found et al. /Forensic
Sri.
ht.
68 (1994)
IYS-203
written such that the entire examination is menu driven once the continuity details and parameters to be measured are entered. The screen comprises two windows: a large uppermost image window, and a lower command window. The margins surrounding these windows change colour according to the type of image being analysed (blue = standard, red = questioned condition). The image window contains that image currently undergoing analysis. It is on this window that the measurement tools are applied. The command window is divided into three regions: (1) the Pixel Indication Grid (PIG) region which is a 5 x 5 pixel enlargement of the area under the cursor in the image window; (2) a text region which provides information to the user as to the stage of the examination and a description of the current parameter to be measured; and (3) a response region which provides the user with a series of buttons which perform functions such as storing the value of the current measured parameter, skipping the measurement, repeating the measurement, or a response to a question posed in the text region. It is through the command window that the handwriting examiner is able to interact with the program. Interaction is critical as the nature of the comparison material is such that the software needs to be guided as to (a) the direction that characters were formed in, (b) when to omit a measurement and (c) when to redo a measurement. 3.3. File manugement section The tile management screen provides a facility for the examiner to enter storage and filing information. The comparison can be given a case number, an examiner code, a reference as to who was overseeing the examination, a date and the name of the individual from whom the standard images were derived. This information not only provides a filing reference for the icon, but appears at the apex of the result sheet generated from PEAT, and ultimately any spreadsheet application into which the results are opened. 3.4. Selecting parameter types This screen provides the user with the range of using the PEAT. The user, to select a parameter, the normal course of a comparison, this stage developed a criteria by which measurements are
parameters that can be measured clicks in the appropriate box. In requires that the examiner has taken.
3.5. Selecting measurement critericr For any given comparison a set of measurement criteria need to be developed. This criteria can be as simple as choosing the particular spatial features that the examiner is interested in. Under the normal scientific protocol it would be desirable to set the type of parameters that would routinely be analysed. This is the topic of current research by the authors. As an example of the type of criteria that could be set, let us consider the image which has nine points where the pixel corresponding
B. Found et al. /Forensic
Sri. ht. 68 (1994)
199
195-203
to turning points, or the start and end of the artifact, can be accurately identified by the examiner. Using these points alone we could measure the variation in the total line length, the total area enclosed by the line, enclosed loops, eight specified line lengths between the points, 36 straight line distances and 28 angles. Clearly these measurements are not all independent of each other: however, it can be seen that a detailed objective spatial measurement range could be generated for a set of standard signatures of this type. The same measurements would be made on the questioned image for comparison purposes. 4. Standard image examination 4.1. Calibrating images Calibration grids accompany every image through the photocopying, and PEAT program. This is desirable for two reasons: (1) if the image is too large or small to be scanned or enlarged, respectively; and (2) since the calibration routine is performed on all calibrated and therefore images generated from analysed in the same sitting. The PEAT calibration method is overviewed in
directly
scanning
it can be either reduced
images the results can be directly mixed enlargement ratios can be Appendix
1.
4.2. Parameter measurement modules The PEAT moves through the parameter modules, at each point prompting the examiner as to what region is to be measured. To determine the total area enclosed within the image, a box is drawn around the image using the click and drag function. This measurement is made automatically. As with all of the PEAT modules there is the opportunity to store, repeat or skip each of the measurements specified in the parameter labelling section. 4.3. The line follow routine (SmartLine) The SmartLine routine was written specifically to measure easily and accurately the length of a non-linear, directional and intersecting line trace. It follows the line, one pixel at a time, in the direction indicated by the user from the designated starting point. 4.4. Measuring areas of enclosed loops This tool allows the user to measure the area of any region of the image that is fully enclosed by that image. It differs from the Total Area function in that it can isolate specific areas of interest. The user is required to click inside the enclosed area. The programme fills this area in red. There is then an option to redo the measurement, to store the measurement or to ADD another area onto that previously calculated. The last of these options is particularly important for handwriting analysis, as in many cases part of the image intersects with the area of interest and effectively sections the area into a number of component parts. The ADD function
200
therefore produces compartmentalised
B. Found et al. /Forensic
Sri.
ht.
68 f 1994)
195-203
a summed result in those cases where the area of interest has been by intersecting strokes.
4.5. Measuring lengths of specified lines This is the distance between two points following the trace of the image. This function uses SmartLine in the same way as the Total Line Length function; however, it does not have the option of adding additional segments. An example of its apphcation would be to measure the curve length of a descending stroke in a letter, e.g. G, where the start and end points would be the uppermost and the lowermost pixel of the G formation. 4.6. Measuring the distance between two points This measurement is the straight line length measured between two points of interest on the image. The start and end points are marked using the PIG. The straight line is automatically drawn in green to illustrate to the user the parameter measured. 4.7. Measuring angles The angle is determined by identifying three points on the image using the PIG window. The first point is marked. The second point is marked and a straight line, drawn in blue on the image, is automatically drawn. When the third point is marked a straight line is drawn between it and the second point. The internal angle at the intersection of these two straight lines is calculated. The option then is to either store the calculated angle or to switch to the external angle and store. 4.8. Questioned image examination Once all of the measurements as dictated by the parametrisation stage have been made for the standard images, the screen refreshes with the background changing from blue to red. The user is required to enter the number of questioned images to be analysed, which sets the number of rows in the results table in which the data will be stored. The examination now repeats using the same prompts as for the standard data. 5. Results The PEAT software produces a results tile automatically, however this is currently designed for importation into a spreadsheet package. For example, to open the results table the user is required to open a program such as ClarisWorks, then open the PEAT results file for the particular case number the user had assigned to it. The spreadsheet then appears containing all of the tiling information, with the columns labelled according to those titles given to them by the user and the rows numbered according to the number of questioned and standard images examined. The questioned and standard images are separated by the automatically calculated statistics for the standard data. The statistics calculated for each parameter on the standard data are:
B. Found et al. /Forensic
(a) (b) (c) (d) (e) (I) (g)
the the the the the the the
Sci. inr. 68 (1994)
sum of the values for the parameter; number of measurements on which the statistics mean; variance; standard deviation; minimum value; and maximum value.
195-203
201
are calculated;
Should these values be required to group with other values, or should more advanced statistical functions need to be performed to suit the particular examination or investigation, then the results can be cut and pasted into other spreadsheets for further analysis. In terms of routine signature comparisons, however, it is thought that the range of variation in the raw data is of particular importance. Other relevant data can also be calculated by comparing the ratios of parameters in the images and by normalising both the questioned and standard images with respect to measurements of relative length, width and height of the images. 6. Errors associated with the technique The possible sources of error associated with techniques of this type are derived from (a) the photocopying process; (b) the scanning process; and (c) the image processing. To attempt to control for these variables, at least in part, all images move through each of these processes at the same time with the same calibration grid. A trial was conducted where one image was photocopied and enlarged ten times. In each case the image was removed from the photocopier and replaced. The ten images were then scanned and analysed using the PEAT software. Fig. 2 represents the error associated with the SmartLine and distance between two points measurement modules. It is thought that small errors in measurements are insignificant when compared to the normal amount of variation associated with handwritten images. 7. Discussion When attempting to simulate a complex questioned signature, two factors must be considered. First the simulation must exhibit spatial features which bear sufficient similarity to the genuine signatures so as not to arouse suspicion. In addition the line quality features must be similar [6]. In any examination of disputed signatures, these elements and others are routinely analysed subjectively by the handwriting examiner. The comparison of line features is well covered in all the document texts [6-91. Objective analysis will enable the examiner to satisfy the requirements of the examination with respect to the determination of the artifacts’ spatial consistency when compared to the standard material. The technique will generate quantities unbiased by the examiner or the protocol used. We believe it will provide information to the examiner conducting routine forensic casework which was not available in a userfriendly dedicated package previously. In addition the measurement technique is de-
B. Found et al. /Forensic
Sri. ht. 68 11994) 195-203
0 0 0
-2 5
00
0.7 0
0.6
0.1 t 0
!
0
I 5
15
10 Mean
Parameter
25
20 Measurement
Fig. 2. Mean parameter
measure
30
35
40
(mm)
vs. f error.
rived from the theory of human motor control and therefore has a basis in pure science. The paradigm within which handwriting examiners work is not well established. Huber and Headrick present a clear argument for the development and inclusion of measurement techniques in forensic handwriting examination. They argue that “Without... [measurement]... handwriting examiners are deluding themselves to claim status for the discipline as science” [5]. It is thought that examinations associated with signature comparisons could be standardised using computer aided objective measurement. The following is a brief description of how a signature examination could be standardised to make at least the comparison process more scientific. In order that a disputed signature be considered consistent to a body of standards it should satisfy criteria developed through controlled research, based on:
(1) the complexity of the formation,
e.g., a simple signature composed of a few lines would be excluded; (2) the spatial consistency score when compared to the population of known images; and assessment of line quality, pen (3) a rigid penalty score based on subjective direction, pen lifts, etc. The score of a particular signature, derived from both objective and subjective methodologies, could dictate to the examiner the level of opinion that could be expressed. Reporting procedures, although relevant to this issue, will not be discussed here.
B. Found et al. /Forensic
Sci. Int. 68 (1994)
195-203
203
8. Conclusion The PEAT software is a tool for those individuals working in forensic handwriting examination that require objective spatial comparison data either for common form analysis or for research applications. Software of this type cannot at this stage hope to replace the expertise of forensic examiners: however, it can provide objective information which is not reliably available through purely visual assessment. Appendix 1. Calibration method Once the image has been opened in PEAT, a prompt instructs the user to place the cross-hairs at the first calibration point, i.e. that point of the calibration scale identifiable by an intersection. As would be expected, a problem arises in that the actual pixel where the intersection occurs is diflicult to accurately hit with the crosshairs. To overcome this the PIG technique was developed. The user is required to click anywhere around the target pixel. When the click has registered, a 5 x 5 pixel window will appear on the upper screen at the point where the cursor was clicked. In the lower command screen a 5 x 5 pixel enlargement of the region underneath the upper pixel window will be displayed. The window can now be moved over the image until the pixel of interest is identified. As the window moves over the image in the top screen so does the pixel enlargement window in the command screen. The centre pixel in this screen is the target pixel and appears red, the balance appearing black or white. When the first calibration point is identified using the above method, the same procedure is prompted to identify the end of the calibration scale. Once this point is identified the user is required to enter the actual length of the portion of the calibration scale measured, e.g. 20, and the units of measurement, e.g. mm. Once the units of measurement are set for the first image, they are locked such that all calibration on images from that point are made in that unit. The PIG technique is used to locate pixels of interest in all of the tools offered for use by PEAT. References 111 0. Hilton, Signatures - review and a new view, J. Forensic Sci., 37 (1992) 125-129. 121 I.W. Evett and R.N. Totty, A study of the variation in the dimensions of genuine signatures. J. Forensic Sci. Sot., 25 (1985) 207-215. [31 R.G. Foley, Characteristics of synchronous 141
151 161 [71 PI 191
sequential signatures. J. Forensic Sci., 32 (1987) 121-129. A.M. Wing and I. Nimmo-Smith, The variability of cursive handwriting measure defined along a continuum: letter specificity. J. Forensic Sci. Sot., 27 (1987) 297-306. R.A. Huber and A.M. Headrick, Let’s do it by numbers. Forensic Sci. Inf., 46 (1990) 209-218. D. Ellen, The Scientific Examination of Documents, Ellis Horwood Ltd., England, 1989, p. 41. 0. Hilton, Scienfijic Examination of Questioned Documents, Elsevier, North Holland, 1982. W.R. Harrison, Suspect Documents: Their Scientific Examination, Sweet and Maxwell Ltd., London, 1966. A.S. Osborn, Questioned Documents, 2nd ed., Boyd Printing Co., New York, 1929.
Forensic Science International 68 (1994) 195-203
A computer program designed to compare spatial elements of handwriting Doug Rogers,
Bryan Found*, Department
OJ Human Biosciences,
Robert
the
Schmittat
La Trobe University. 607 Swanston Street, Auslralia 3053
Carlton South,
Victoria,
Received 20 April 1994; accepted 2 June 1994
Abstract The comparison of questioned and standard line traces in forensic handwriting examination has to date been based almost entirely on subjective techniques. Handwriting examiners have not been equipped with a basic user-friendly technique to perform measurements on what are non-linear and variable behavioural artifacts. This paper describes a technique developed through research into human motor control which has been modified to be used by forensic handwriting examiners. The program provides a series of measurement tools. These tools can be applied to scanned images for the purpose of determining the spatial consistency of a disputed sample with a body of known writings. It is thought that the immediate application for this technique in the forensic casework environment is for the comparison of disputed signatures. In addition, the program can be used for any forensic research project requiring objective spatial data. If the field of forensic handwriting examination is to be considered a scientific endeavour, then the move toward the inclusion of objective measurement as part of the overall comparison methodology must be made. Keywords:
Image
processing;
Objective
analysis;
Spatial
data;
Signatures;
Document
examination
1. Introduction The field of routine almost
total
absence
of a questioned
forensic
handwriting
of objective
data
image
in comparison
comparison
has always
to aid in the determination to a group
of known
writings.
* Corresponding author 0379-0738/94/$07.00 0 1994 Elsevier Science Ireland SSDI
0379-0738(94)01558-M
suffered
Ltd. All rights reserved
from an
of the consistency Hilton
clearly
196
B. Found et al. /Forensic
Sci. ht. 68 (1994)
195-203
states “We are concerned in every signature problem with whether the specimen before us is consistent with the variable group of signatures that the person is capable of producing or normally uses to represent himself or herself’ [ 11. Opinions as to consistency should maximise the use of objective comparison techniques. It is well known that handwriting measurement has been employed by researchers in signature verification techniques and database searching strategies. The thrust of this paper is, however, toward a measurement tool that can be applied to routine signature comparisons. Of particular relevance is the work conducted on the statistical analysis of handwriting features and their variations [2-41. In a scientific sense, objective techniques can offer a powerful input into any examination. Objective techniques will provide numerical answers to questions as to whether a particular spatial element falls within the variation of a group of known material. Instrumental techniques facilitate reproducibility of results, given the same material. Data of this type can be used to develop criteria on which levels of opinion can be expressed. Criteria can be developed which provide indicators of the complexity of signatures, which is related to the degree of difficulty associated with copying a given image. Clearly the potential for objective techniques in routine casework and developmental research is enormous. The importance of this type of approach is well summarised in the following passage: If we have any hope of achieving accuracy and precision in examination results, any wish to serve the judicial system as we should, any aspiration to acquire the mantle of science, we must embark on the pursuit of measurement in handwriting identification. [5]
The software described in this report was designed for the purpose of providing a technique that could make objective measurements from two-dimensional static images, taking into account the path that the image was formed in. Handwriting generates such images. Spatial measurements of the artifact has always been difficult by virtue of the non-linear nature of many of the parameters required to be measured and the tendency for the path of one section of the line to overlap with previously formed sections. Simple pixel counting software produces errors related to the overlapping sections and associated with the relative alignment of screen pixels. The software we have developed for forensic applications we have called the Pattern Evidence Analysis Toolbox (PEAT). The PEAT software is a user-friendly package providing tools which enable handwriting examiners to accurately measure the total line length, the total area enclosed by the line, the area of any enclosed region, the path length between any two points, the straight line distance between any two points and angles directly from scanned images. It is structured in a normal standard image to questioned image comparison format. The results of any comparison will provide the examiner with a clear profile of what spatial features fall within or outside of the variation of the given body of standard material. 2. Equipment The PEAT as it is being currently
used requires
hardware
in the form of an Apple
B. Found et al. /Forensic
Sci. ht. 68 (1994)
197
195-203
Macintosh computer (series II or above) and an Apple One Scanner (300 d.p.i or greater). The software requirements are the PEAT, an image processing package (Image 1.41) and a spreadsheet package (ClarisWorks). 3. Method 3.1. Image preparation Images requiring analysis are enlarged on a photocopier so as to approximately tit across an A4 sheet of paper. A calibration grid accompanies each image through the enlargement process. The enlarged images are then scanned into a computer and saved as a PICT file. Once all images have been scanned they are processed using Image 1.41 software. A routine such as density slicing is carried out on the image to set upper and lower grey scale limits that will result in the image appearing as a complete and continuous line. Under normal circumstances, a simple threshold routine will accomplish this. Images are then converted to a binary form by setting the image pixels to black and all other pixels to white. A skeletonisation routine is applied which reduces the lines in the image to a thickness of one pixel. The processed images are saved in a MacPaint format. 3.2. The PEAT technique The overall structure of the PEAT technique is represented in Fig. 1. The format is based on a typical questioned to standard forensic comparison.-The program is
\ f PARAMETERISATION I
ANALYSIS-
( Fig. 1. Structure
of the PEAT program.
RESULTS
1
198
B. Found et al. /Forensic
Sri.
ht.
68 (1994)
IYS-203
written such that the entire examination is menu driven once the continuity details and parameters to be measured are entered. The screen comprises two windows: a large uppermost image window, and a lower command window. The margins surrounding these windows change colour according to the type of image being analysed (blue = standard, red = questioned condition). The image window contains that image currently undergoing analysis. It is on this window that the measurement tools are applied. The command window is divided into three regions: (1) the Pixel Indication Grid (PIG) region which is a 5 x 5 pixel enlargement of the area under the cursor in the image window; (2) a text region which provides information to the user as to the stage of the examination and a description of the current parameter to be measured; and (3) a response region which provides the user with a series of buttons which perform functions such as storing the value of the current measured parameter, skipping the measurement, repeating the measurement, or a response to a question posed in the text region. It is through the command window that the handwriting examiner is able to interact with the program. Interaction is critical as the nature of the comparison material is such that the software needs to be guided as to (a) the direction that characters were formed in, (b) when to omit a measurement and (c) when to redo a measurement. 3.3. File manugement section The tile management screen provides a facility for the examiner to enter storage and filing information. The comparison can be given a case number, an examiner code, a reference as to who was overseeing the examination, a date and the name of the individual from whom the standard images were derived. This information not only provides a filing reference for the icon, but appears at the apex of the result sheet generated from PEAT, and ultimately any spreadsheet application into which the results are opened. 3.4. Selecting parameter types This screen provides the user with the range of using the PEAT. The user, to select a parameter, the normal course of a comparison, this stage developed a criteria by which measurements are
parameters that can be measured clicks in the appropriate box. In requires that the examiner has taken.
3.5. Selecting measurement critericr For any given comparison a set of measurement criteria need to be developed. This criteria can be as simple as choosing the particular spatial features that the examiner is interested in. Under the normal scientific protocol it would be desirable to set the type of parameters that would routinely be analysed. This is the topic of current research by the authors. As an example of the type of criteria that could be set, let us consider the image which has nine points where the pixel corresponding
B. Found et al. /Forensic
Sri. ht. 68 (1994)
199
195-203
to turning points, or the start and end of the artifact, can be accurately identified by the examiner. Using these points alone we could measure the variation in the total line length, the total area enclosed by the line, enclosed loops, eight specified line lengths between the points, 36 straight line distances and 28 angles. Clearly these measurements are not all independent of each other: however, it can be seen that a detailed objective spatial measurement range could be generated for a set of standard signatures of this type. The same measurements would be made on the questioned image for comparison purposes. 4. Standard image examination 4.1. Calibrating images Calibration grids accompany every image through the photocopying, and PEAT program. This is desirable for two reasons: (1) if the image is too large or small to be scanned or enlarged, respectively; and (2) since the calibration routine is performed on all calibrated and therefore images generated from analysed in the same sitting. The PEAT calibration method is overviewed in
directly
scanning
it can be either reduced
images the results can be directly mixed enlargement ratios can be Appendix
1.
4.2. Parameter measurement modules The PEAT moves through the parameter modules, at each point prompting the examiner as to what region is to be measured. To determine the total area enclosed within the image, a box is drawn around the image using the click and drag function. This measurement is made automatically. As with all of the PEAT modules there is the opportunity to store, repeat or skip each of the measurements specified in the parameter labelling section. 4.3. The line follow routine (SmartLine) The SmartLine routine was written specifically to measure easily and accurately the length of a non-linear, directional and intersecting line trace. It follows the line, one pixel at a time, in the direction indicated by the user from the designated starting point. 4.4. Measuring areas of enclosed loops This tool allows the user to measure the area of any region of the image that is fully enclosed by that image. It differs from the Total Area function in that it can isolate specific areas of interest. The user is required to click inside the enclosed area. The programme fills this area in red. There is then an option to redo the measurement, to store the measurement or to ADD another area onto that previously calculated. The last of these options is particularly important for handwriting analysis, as in many cases part of the image intersects with the area of interest and effectively sections the area into a number of component parts. The ADD function
200
therefore produces compartmentalised
B. Found et al. /Forensic
Sri.
ht.
68 f 1994)
195-203
a summed result in those cases where the area of interest has been by intersecting strokes.
4.5. Measuring lengths of specified lines This is the distance between two points following the trace of the image. This function uses SmartLine in the same way as the Total Line Length function; however, it does not have the option of adding additional segments. An example of its apphcation would be to measure the curve length of a descending stroke in a letter, e.g. G, where the start and end points would be the uppermost and the lowermost pixel of the G formation. 4.6. Measuring the distance between two points This measurement is the straight line length measured between two points of interest on the image. The start and end points are marked using the PIG. The straight line is automatically drawn in green to illustrate to the user the parameter measured. 4.7. Measuring angles The angle is determined by identifying three points on the image using the PIG window. The first point is marked. The second point is marked and a straight line, drawn in blue on the image, is automatically drawn. When the third point is marked a straight line is drawn between it and the second point. The internal angle at the intersection of these two straight lines is calculated. The option then is to either store the calculated angle or to switch to the external angle and store. 4.8. Questioned image examination Once all of the measurements as dictated by the parametrisation stage have been made for the standard images, the screen refreshes with the background changing from blue to red. The user is required to enter the number of questioned images to be analysed, which sets the number of rows in the results table in which the data will be stored. The examination now repeats using the same prompts as for the standard data. 5. Results The PEAT software produces a results tile automatically, however this is currently designed for importation into a spreadsheet package. For example, to open the results table the user is required to open a program such as ClarisWorks, then open the PEAT results file for the particular case number the user had assigned to it. The spreadsheet then appears containing all of the tiling information, with the columns labelled according to those titles given to them by the user and the rows numbered according to the number of questioned and standard images examined. The questioned and standard images are separated by the automatically calculated statistics for the standard data. The statistics calculated for each parameter on the standard data are:
B. Found et al. /Forensic
(a) (b) (c) (d) (e) (I) (g)
the the the the the the the
Sci. inr. 68 (1994)
sum of the values for the parameter; number of measurements on which the statistics mean; variance; standard deviation; minimum value; and maximum value.
195-203
201
are calculated;
Should these values be required to group with other values, or should more advanced statistical functions need to be performed to suit the particular examination or investigation, then the results can be cut and pasted into other spreadsheets for further analysis. In terms of routine signature comparisons, however, it is thought that the range of variation in the raw data is of particular importance. Other relevant data can also be calculated by comparing the ratios of parameters in the images and by normalising both the questioned and standard images with respect to measurements of relative length, width and height of the images. 6. Errors associated with the technique The possible sources of error associated with techniques of this type are derived from (a) the photocopying process; (b) the scanning process; and (c) the image processing. To attempt to control for these variables, at least in part, all images move through each of these processes at the same time with the same calibration grid. A trial was conducted where one image was photocopied and enlarged ten times. In each case the image was removed from the photocopier and replaced. The ten images were then scanned and analysed using the PEAT software. Fig. 2 represents the error associated with the SmartLine and distance between two points measurement modules. It is thought that small errors in measurements are insignificant when compared to the normal amount of variation associated with handwritten images. 7. Discussion When attempting to simulate a complex questioned signature, two factors must be considered. First the simulation must exhibit spatial features which bear sufficient similarity to the genuine signatures so as not to arouse suspicion. In addition the line quality features must be similar [6]. In any examination of disputed signatures, these elements and others are routinely analysed subjectively by the handwriting examiner. The comparison of line features is well covered in all the document texts [6-91. Objective analysis will enable the examiner to satisfy the requirements of the examination with respect to the determination of the artifacts’ spatial consistency when compared to the standard material. The technique will generate quantities unbiased by the examiner or the protocol used. We believe it will provide information to the examiner conducting routine forensic casework which was not available in a userfriendly dedicated package previously. In addition the measurement technique is de-
B. Found et al. /Forensic
Sri. ht. 68 11994) 195-203
0 0 0
-2 5
00
0.7 0
0.6
0.1 t 0
!
0
I 5
15
10 Mean
Parameter
25
20 Measurement
Fig. 2. Mean parameter
measure
30
35
40
(mm)
vs. f error.
rived from the theory of human motor control and therefore has a basis in pure science. The paradigm within which handwriting examiners work is not well established. Huber and Headrick present a clear argument for the development and inclusion of measurement techniques in forensic handwriting examination. They argue that “Without... [measurement]... handwriting examiners are deluding themselves to claim status for the discipline as science” [5]. It is thought that examinations associated with signature comparisons could be standardised using computer aided objective measurement. The following is a brief description of how a signature examination could be standardised to make at least the comparison process more scientific. In order that a disputed signature be considered consistent to a body of standards it should satisfy criteria developed through controlled research, based on:
(1) the complexity of the formation,
e.g., a simple signature composed of a few lines would be excluded; (2) the spatial consistency score when compared to the population of known images; and assessment of line quality, pen (3) a rigid penalty score based on subjective direction, pen lifts, etc. The score of a particular signature, derived from both objective and subjective methodologies, could dictate to the examiner the level of opinion that could be expressed. Reporting procedures, although relevant to this issue, will not be discussed here.
B. Found et al. /Forensic
Sci. Int. 68 (1994)
195-203
203
8. Conclusion The PEAT software is a tool for those individuals working in forensic handwriting examination that require objective spatial comparison data either for common form analysis or for research applications. Software of this type cannot at this stage hope to replace the expertise of forensic examiners: however, it can provide objective information which is not reliably available through purely visual assessment. Appendix 1. Calibration method Once the image has been opened in PEAT, a prompt instructs the user to place the cross-hairs at the first calibration point, i.e. that point of the calibration scale identifiable by an intersection. As would be expected, a problem arises in that the actual pixel where the intersection occurs is diflicult to accurately hit with the crosshairs. To overcome this the PIG technique was developed. The user is required to click anywhere around the target pixel. When the click has registered, a 5 x 5 pixel window will appear on the upper screen at the point where the cursor was clicked. In the lower command screen a 5 x 5 pixel enlargement of the region underneath the upper pixel window will be displayed. The window can now be moved over the image until the pixel of interest is identified. As the window moves over the image in the top screen so does the pixel enlargement window in the command screen. The centre pixel in this screen is the target pixel and appears red, the balance appearing black or white. When the first calibration point is identified using the above method, the same procedure is prompted to identify the end of the calibration scale. Once this point is identified the user is required to enter the actual length of the portion of the calibration scale measured, e.g. 20, and the units of measurement, e.g. mm. Once the units of measurement are set for the first image, they are locked such that all calibration on images from that point are made in that unit. The PIG technique is used to locate pixels of interest in all of the tools offered for use by PEAT. References 111 0. Hilton, Signatures - review and a new view, J. Forensic Sci., 37 (1992) 125-129. 121 I.W. Evett and R.N. Totty, A study of the variation in the dimensions of genuine signatures. J. Forensic Sci. Sot., 25 (1985) 207-215. [31 R.G. Foley, Characteristics of synchronous 141
151 161 [71 PI 191
sequential signatures. J. Forensic Sci., 32 (1987) 121-129. A.M. Wing and I. Nimmo-Smith, The variability of cursive handwriting measure defined along a continuum: letter specificity. J. Forensic Sci. Sot., 27 (1987) 297-306. R.A. Huber and A.M. Headrick, Let’s do it by numbers. Forensic Sci. Inf., 46 (1990) 209-218. D. Ellen, The Scientific Examination of Documents, Ellis Horwood Ltd., England, 1989, p. 41. 0. Hilton, Scienfijic Examination of Questioned Documents, Elsevier, North Holland, 1982. W.R. Harrison, Suspect Documents: Their Scientific Examination, Sweet and Maxwell Ltd., London, 1966. A.S. Osborn, Questioned Documents, 2nd ed., Boyd Printing Co., New York, 1929.