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Quality Transmission of Additional Image Information by 2D Image Basis
ELSEVIER
Copyright © IF AC Programmable Devices and Systems, Ostrava, Czech Republic, 2003
IFAC PUBLICATIONS www.elsevier.comllocate/ifac
QUALITY TRANSMISSION OF ADDITIONAL IMAGE INFORMATION BY 2D IMAGE BASIS Miroslav Hrianka, Marek Slusarcik, University of Zilina, Vel'kj diel, 010 26 Zilina, Slovak Republic [email protected]
Abstract: This paper deals with problem of transport of additional image information by image matrix of basic 2D image. The subject of analysis is focused on gray and color basic 2D images, with additional binary image. The paper introduces methods of additional image transmission as well as conditions for successful import and export of additional image processing. Main mean of access problem solving are histogram properties of images. There are shown different methods of applications and corresponding results. Copyright © 2003 IFAC Keywords: image analysis, image distortion, image restoration, transmission, matrix elements, binary images, histograms
1. INTRODUCTION
2. TRANSMISSION METHODS OF ADDITIONAL IMAGE INFORMATION
The senses are the primary source of information for human beings. Sight, for man, is his sole source of image information. The development of science and technology has brought a whole range of tasks which are connected with the need for processing and evaluation of image information. Image processing has become a profession in various areas of science and technology. Creating, archiving and transmission of image information is now a fundamental part of our life. A digital signal, in comparison with an analogue one is more simple to archive, transmit and easier to protect against faults and misuse. In this paper we will be focusing on the transmission of additional information in the image matrix of a digital image. The possibilities of transmission of additional information in various histogram intervals of the basic image were also analyzed. The aim is to use the basic digital image as the as a mean of transmission of additional information. The basic requirement is to create a methodology of total or almost complete image reconstruction of the additional information.
The transmission of additional information uses the histogram analysis of a basic 2D image. The software product LUCIA has been used to create the image analysis methodology. This program has been designed for processing and analysis of basic image [2]. The image histogram, by the use of a graph, displays a sum of basic image elements which have the same value intensity in the whole screen matrix. In a color image there are RGB (HSL) components. As histograms have mostly a nonlinear fonn, the occurrence of local and global min or max may be assumed. These parts of the histograms may be used to transmit added information. The simplest way is to use a binary image. Another possibility is to use a gray or color image. The most simple method is the insertion of an additional binary image to the beginning or end of the histogram Another possibility is to insert a binary image in positions where the histogram reaches a local minimum (Fig. 1) i.e. using levels which are minimally used in the image itself. Next possibility is using levels which are used to the maximum value intensities of the histogram (Fig. 2). 277
3. METHODOLOGY OF TRANSMISSION OF ADDITIONAL IMAGE INFORMA nON
For the verification of the experiment, as basic the gray image "Lenna" (Fig. 5) was used, as the additional binary image information was used "Logo" (Fig. 6).
o' '20 ' '40 ' 'so" 80 ' ,ioo' 'lio' '140' iso' i80 '200' iio' i40,' '25,5 Fig, I Histogram local minimum
Fig, 2 Histogram local maximum Alternatively, it is possible to use filtering a narrow band intensity level in minimum "min-gap" (Fig, 3) or maximum "max-gap" (Fig. 4) intensity level position of the histogram and insert additional binary image into the positions mentioned before.
Fig. 5 Basic gray image "Lenna"
Fig. 3 Histogram min-gap intensity
Fig, 6 Additional binary image "Logo"
1
j
J
From the examples mentioned from the previous chapter, several combinations of inserting additional image can be created. For the presentation of the results from individual methods it is possible to focus attention on the basic gray image "Lenna" (Fig. 5) with 256 intensity levels and 800x600 pixels resolution. The binary image "Logo" (Fig. 6) has the same pixe\s resolution, two binary intensity levels were changed. The binary image was used during of the experiments in invert form as complement Fig. 6. To present the results of the experiments while using this basic color image ,,Lenna", is not technically possible in this article due to printing restraints. While using the histogram, it is basically to place the binary image in the area of the beginning or the end of the histogram, or to divide the binary levels so that the lower level is placed at the beginning and the higher level at the end of the histogram. The results confirmed that the export of the additional image is satisfactory, however the resulting image is noticeably distorted after the importing of the additional
~~ub~~._
o' '20' .40' .so' .80' .io'o '120' '140' iSo' i80 .200' 2io' i40,' '25,5 Fig. 4 Histogram max-gap intensity Various types of coding of a binary image into a histogram are included in more complex methods. An important criteria in these methods of inserting additional information is the requirement that the added information does not distort or change the original transmitted image. This condition does not relate to the histogram as by inserting the binary image the histogram is changed. The basic requirement is to create a way of inserting (import) of additional information into the basic 2D image so that the original image perfectly masks the presence of the inserted image. The next most important requirement is that the inserted image is not destroyed after the decoding (export) of the original basic image.
278
image. This is why the practical use of this procedure is therefor not usable. In the next experiments the binary image "Logo" was placed in areas of min and max level of the histogram of the gray image "Lenna", where the difference binary levels of the image "Logo" was only one step. For practical reasons, the binary image was used in an inverted form. The results were noticeably better that in the previous cases, particularly in the phase of the importation of the additional binary picture.
357585
o
20
40
60
80
100 120 140 160 180 200 220 240
25~
4. IMPROYMENT OF QUALITY TRANSMISSION
The quality of coding was improved by using image operation shading which is used for corrections of nonhomogenity of a captured image matrix [2]. During the coding process a binary image was used as a "reference image" and the "current image" was a gray image. The algorithm of the operation uses multiple correction coefficient from point to point for the whole image matrix. The value of the corrected coefficient is directly proportional to the corresponding value of the shading image. The alternative possibility is to use correcting subtractive coefficients. The results of the decoded the binary image from the basic gray image are shown in pictures showing the various levels of binary intensity (Fig. 7, 8, 9).
Fig. 8 Decoded additional image, levels 102-103
Where the binary image has values of 51 - 52 intensil levels, the quality of the decoding is very good.
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o
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100 120 140 160 180 200 220 240 255
o
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100 120 140 160 180 200 220 240 255
Fig. 7 Decoded additional image, levels 153-154
Fig. 9 Decoded additional image, levels 51-52
Where the binary image has values of intensity levels 153 - 154, the quality of decoding of the image is decidedly affected by the intensity levels of the basic image. Where the levels are 102 - 103, the decoding is slightly distorted in areas where the intensity levels of the basic pictures is close.
To find the optimal level of binary image nee< a number of experiments. A similar methodology may also be applied if the bas image was color with the possibility of more detaik precision of conditions for individual color componen of the basic image.
279
From the above mentioned examples, the most suitable intensity level of the binary image "Logo" is the one with values of 51 - 52 intensity levels. Shading operation (comment) [2]: Performs shading correction on current color image using the shading image defined by the Set Shading Image command. Comments The shading image should correspond to an image of homogenous background (for transmitting light it is non-absorbing media). The shading image can be used as a correction image. If we employ Shading correction in Grabbing command a non-homogenous illumination can be corrected. nrtfiJ.ft@ §iii
xl R.d
Ope!iIllOl"l
wa. .
Fig. 10 Function
CONCLUSION In this paper the transmission possibilities of additional image information in defined intervals of a histogram of a basic gray image have been presented. The aim was to verify a suitable methodology for the transmission of an additional binary image in the image matrix of a basic two dimensional image. A binary image "Logo" as additional image information was inserted under defined conditions into a gray basic image "Lenna". The quality of coding was significantly improved by applying an image operation "shading" which is used as standard procedure to correct non-homogenity of a captured image matrix. Also covered in this paper were parameters and conditions needed for the application of the experiment. The software program "LUCIA" which is designed for the processing and analysis an image was used during the analysis of the results. Acknowledgement: This work was supported by the grant NO.1I0144/03 from VEGA grant agency. REFERENCES Kulla, P. (2000). Employing of Images as NonVisible Textures Carriers. In: Proceedings "Radioelektronika 2000 ", pp.i2i-i22 STU Bratislava, September 2000 Laboratory Imaging, Praha (2001). LUCIA, Function Reference, LIM Praha The third Eye (2002). http://www.webkclub.com Steganos security (2002). http://www.steganos.com. 280
Copyright © IF AC Programmable Devices and Systems, Ostrava, Czech Republic, 2003
IFAC PUBLICATIONS www.elsevier.comllocate/ifac
QUALITY TRANSMISSION OF ADDITIONAL IMAGE INFORMATION BY 2D IMAGE BASIS Miroslav Hrianka, Marek Slusarcik, University of Zilina, Vel'kj diel, 010 26 Zilina, Slovak Republic [email protected]
Abstract: This paper deals with problem of transport of additional image information by image matrix of basic 2D image. The subject of analysis is focused on gray and color basic 2D images, with additional binary image. The paper introduces methods of additional image transmission as well as conditions for successful import and export of additional image processing. Main mean of access problem solving are histogram properties of images. There are shown different methods of applications and corresponding results. Copyright © 2003 IFAC Keywords: image analysis, image distortion, image restoration, transmission, matrix elements, binary images, histograms
1. INTRODUCTION
2. TRANSMISSION METHODS OF ADDITIONAL IMAGE INFORMATION
The senses are the primary source of information for human beings. Sight, for man, is his sole source of image information. The development of science and technology has brought a whole range of tasks which are connected with the need for processing and evaluation of image information. Image processing has become a profession in various areas of science and technology. Creating, archiving and transmission of image information is now a fundamental part of our life. A digital signal, in comparison with an analogue one is more simple to archive, transmit and easier to protect against faults and misuse. In this paper we will be focusing on the transmission of additional information in the image matrix of a digital image. The possibilities of transmission of additional information in various histogram intervals of the basic image were also analyzed. The aim is to use the basic digital image as the as a mean of transmission of additional information. The basic requirement is to create a methodology of total or almost complete image reconstruction of the additional information.
The transmission of additional information uses the histogram analysis of a basic 2D image. The software product LUCIA has been used to create the image analysis methodology. This program has been designed for processing and analysis of basic image [2]. The image histogram, by the use of a graph, displays a sum of basic image elements which have the same value intensity in the whole screen matrix. In a color image there are RGB (HSL) components. As histograms have mostly a nonlinear fonn, the occurrence of local and global min or max may be assumed. These parts of the histograms may be used to transmit added information. The simplest way is to use a binary image. Another possibility is to use a gray or color image. The most simple method is the insertion of an additional binary image to the beginning or end of the histogram Another possibility is to insert a binary image in positions where the histogram reaches a local minimum (Fig. 1) i.e. using levels which are minimally used in the image itself. Next possibility is using levels which are used to the maximum value intensities of the histogram (Fig. 2). 277
3. METHODOLOGY OF TRANSMISSION OF ADDITIONAL IMAGE INFORMA nON
For the verification of the experiment, as basic the gray image "Lenna" (Fig. 5) was used, as the additional binary image information was used "Logo" (Fig. 6).
o' '20 ' '40 ' 'so" 80 ' ,ioo' 'lio' '140' iso' i80 '200' iio' i40,' '25,5 Fig, I Histogram local minimum
Fig, 2 Histogram local maximum Alternatively, it is possible to use filtering a narrow band intensity level in minimum "min-gap" (Fig, 3) or maximum "max-gap" (Fig. 4) intensity level position of the histogram and insert additional binary image into the positions mentioned before.
Fig. 5 Basic gray image "Lenna"
Fig. 3 Histogram min-gap intensity
Fig, 6 Additional binary image "Logo"
1
j
J
From the examples mentioned from the previous chapter, several combinations of inserting additional image can be created. For the presentation of the results from individual methods it is possible to focus attention on the basic gray image "Lenna" (Fig. 5) with 256 intensity levels and 800x600 pixels resolution. The binary image "Logo" (Fig. 6) has the same pixe\s resolution, two binary intensity levels were changed. The binary image was used during of the experiments in invert form as complement Fig. 6. To present the results of the experiments while using this basic color image ,,Lenna", is not technically possible in this article due to printing restraints. While using the histogram, it is basically to place the binary image in the area of the beginning or the end of the histogram, or to divide the binary levels so that the lower level is placed at the beginning and the higher level at the end of the histogram. The results confirmed that the export of the additional image is satisfactory, however the resulting image is noticeably distorted after the importing of the additional
~~ub~~._
o' '20' .40' .so' .80' .io'o '120' '140' iSo' i80 .200' 2io' i40,' '25,5 Fig. 4 Histogram max-gap intensity Various types of coding of a binary image into a histogram are included in more complex methods. An important criteria in these methods of inserting additional information is the requirement that the added information does not distort or change the original transmitted image. This condition does not relate to the histogram as by inserting the binary image the histogram is changed. The basic requirement is to create a way of inserting (import) of additional information into the basic 2D image so that the original image perfectly masks the presence of the inserted image. The next most important requirement is that the inserted image is not destroyed after the decoding (export) of the original basic image.
278
image. This is why the practical use of this procedure is therefor not usable. In the next experiments the binary image "Logo" was placed in areas of min and max level of the histogram of the gray image "Lenna", where the difference binary levels of the image "Logo" was only one step. For practical reasons, the binary image was used in an inverted form. The results were noticeably better that in the previous cases, particularly in the phase of the importation of the additional binary picture.
357585
o
20
40
60
80
100 120 140 160 180 200 220 240
25~
4. IMPROYMENT OF QUALITY TRANSMISSION
The quality of coding was improved by using image operation shading which is used for corrections of nonhomogenity of a captured image matrix [2]. During the coding process a binary image was used as a "reference image" and the "current image" was a gray image. The algorithm of the operation uses multiple correction coefficient from point to point for the whole image matrix. The value of the corrected coefficient is directly proportional to the corresponding value of the shading image. The alternative possibility is to use correcting subtractive coefficients. The results of the decoded the binary image from the basic gray image are shown in pictures showing the various levels of binary intensity (Fig. 7, 8, 9).
Fig. 8 Decoded additional image, levels 102-103
Where the binary image has values of 51 - 52 intensil levels, the quality of the decoding is very good.
357585
357585
o
20
40
60
80
100 120 140 160 180 200 220 240 255
o
20
40
60
80
100 120 140 160 180 200 220 240 255
Fig. 7 Decoded additional image, levels 153-154
Fig. 9 Decoded additional image, levels 51-52
Where the binary image has values of intensity levels 153 - 154, the quality of decoding of the image is decidedly affected by the intensity levels of the basic image. Where the levels are 102 - 103, the decoding is slightly distorted in areas where the intensity levels of the basic pictures is close.
To find the optimal level of binary image nee< a number of experiments. A similar methodology may also be applied if the bas image was color with the possibility of more detaik precision of conditions for individual color componen of the basic image.
279
From the above mentioned examples, the most suitable intensity level of the binary image "Logo" is the one with values of 51 - 52 intensity levels. Shading operation (comment) [2]: Performs shading correction on current color image using the shading image defined by the Set Shading Image command. Comments The shading image should correspond to an image of homogenous background (for transmitting light it is non-absorbing media). The shading image can be used as a correction image. If we employ Shading correction in Grabbing command a non-homogenous illumination can be corrected. nrtfiJ.ft@ §iii
xl R.d
Ope!iIllOl"l
wa. .
Fig. 10 Function
CONCLUSION In this paper the transmission possibilities of additional image information in defined intervals of a histogram of a basic gray image have been presented. The aim was to verify a suitable methodology for the transmission of an additional binary image in the image matrix of a basic two dimensional image. A binary image "Logo" as additional image information was inserted under defined conditions into a gray basic image "Lenna". The quality of coding was significantly improved by applying an image operation "shading" which is used as standard procedure to correct non-homogenity of a captured image matrix. Also covered in this paper were parameters and conditions needed for the application of the experiment. The software program "LUCIA" which is designed for the processing and analysis an image was used during the analysis of the results. Acknowledgement: This work was supported by the grant NO.1I0144/03 from VEGA grant agency. REFERENCES Kulla, P. (2000). Employing of Images as NonVisible Textures Carriers. In: Proceedings "Radioelektronika 2000 ", pp.i2i-i22 STU Bratislava, September 2000 Laboratory Imaging, Praha (2001). LUCIA, Function Reference, LIM Praha The third Eye (2002). http://www.webkclub.com Steganos security (2002). http://www.steganos.com. 280