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The detection of unresolved targets using the hough transform
ABSTRACTS
OF
PAPERS
ACCEPTED
FOR
PUBLICATION
197
A Spatio-Temporal Gradient Method for Estimating the Dkptbcement Field in Time- Varying Imagery. R. PAQUIN AND E. DUBOIS. INRS-Telecommunications, 3 Place du Commerce, Ile des Soeurs, Quebec, Canada, H3E 1H6. Received February 18, 1982; revised July 16, 1982. The displacement between successive frames of each picture element in an image sequence forms a two-dimensional vector field called the displacement field (or optical flow). This paper presents an algorithm for estimating the displacement field, based on a constraint equation relating the spatial gradient to a temporal directional derivative for a moving object. The estimate for a given picture element is obtained by updating the estimate for the corresponding picture element in the previous frame, using information in a three-dimensional block centered on the picture element of interest. The performance of this estimator has been tested on a number of sequences of real imagery, both with artificial displacements and with natural motion, and the main parameters of the estimator have been optimized. It has been found to be accurate, and robust in the presence of noise. A number of simplifications to reduce the computational complexity of the algorithm have been proposed, and their effects on performance have been studied.
Unakstanding Blood Cell Motion. MARTIN D. LEVINE AND YOUSSRY and Graphics Laboratory, Department of Electrical Engineering. Dentistry, McGill University, Montreal, Quebec, Canada. Received 1982.
M. YOUSSEF. Computer Vision PETER B. NOBLE, Faculty of March 1, 1982; revised July 7,
The main function of the surface of a blood cell is to receive information from the environment. Experiments have indicated that the cell membrane plays a vital role in the life, development, and regulation of cells. However, there is no existing method to quantify the observable changes in membrane shape that occur in locomotion. The main goal of this research is to develop an image interpretation system capable of analyzing the structural changes in the morphology of cells from a sequence of pictures, using automatic techniques of image processing. A model for a general dynamic scene analysis system is described. It consists of three basic entities: dynamic data, static data, and a collection of analysis processes. Based on this model, we have implemented a rule-based image interpretation system for moving cells. The system consists of different cooperating computational processes, which interact with two common memories, a short term memory (STM) and a long term memory (LTM). The STM contains a dynamic record of the instantaneous cell motion, shape, and structural changes, as well as the current global description of the cell behaviour. The LTM data are static and are implemented as rules. These describe the general model of the morphology of the cells under analysis, as well as control information pertinent to the computational processes. The latter are activated by the control rules throughout the three hierarchical analysis stages: static, incremental and global. They interact through the STM using the information stored in the LTM, until a complete description of the dynamic cell motion and morphology is obtained. The system has been successfully employed to analyze and study the pseudopod kinetics of white blood cells.
S. N. JAYARAMAMLJRTHY AND RAMESH An Approach to the Segmentation of Textured Dynamic Scenes. JAIN. Intelligent Systems Laboratory, Department of Computer Science, Wayne State University, Detroit, Michigan 48202. Received March 8, 1982; revised July 20, 1982. This moving regions used to and the illustrate indicator
paper presents an approach for the segmentation of dynamic scenes containing textured objects against a textured background. This multistage approach first uses differencing to obtain active in the frame which contain moving objects. In the next stage, a Hough transform technique is determine the motion parameters associated with each active region. Finally, the intensity changes motion parameters are combined to obtain the masks of the moving objects. Our experiments the efficacy of the approach for moving textured objects even in the presence of occlusion. An that signals the presence of the rotational component of the object motion can also be extracted.
ALAN E. COWART. Research Triangle The Detection of Unresohwd Targets Using the Hough Transform. Institute, North Carolina State University, Raleigh, North Carolina 27650. WESLEY E. SNYDER. W. HOWARD RUEDGER. Rese‘arch North Carolina State University, Raleigh, North Carolina 27650. Triangle Institute. Received March 8, 1982; revised July 21, 1982.
Clutter resulting from drift and vibration in a sensor’s line-of-sight and time-varying components in the background can seriously hinder the detection of faint, unresolved (i.e., point) targets moving against a background. However, these targets produce well-defined patterns of motion referred to as tracks whereas the effects of noise and clutter are more random. Frame-to-frame differencing can be used to reject clutter and enhance the detection of moving targets. These difference frames can then be combined recursively to form target tracks. The tracks of nonmaneuvering (i.e., constant velocity) targets appear as line segments that can be detected using the Hough transform. In addition, the current position and heading of a target can be determined using a technique based on matched filtering. An example demonstrating the performance of this technique is also presented. On Sequential and Pardel Node-Rewithg Grrcgrl, Gmnnasrs, II. D. JANSENS AND R. VERRAEDT. Department of Mathematics, U.I.A., University of Antwerp, B-2610 Wilrijk, Belgium. Cr. ROZEN~ERG. Institute of Applied Mathematics and Computer Science, University of Leiden, The Netherlands. Received July 12, 1982. This paper directly continues research initiated in Computer Graphics and Image Processing, 18 (19823. Several new aspects of the relationship between a comection relation mechanism and a stencil mechanism used for specifying embeddings in graph grammars are considered. NOTES and Metho& of H&gram Modification Aabpted for V&al Perception Fu - NIAN Ku. Shanghai Jiao Tong University, Shanghai, China Received July 6, 1981; revised January 22 and July 12, 1982.
The Principks
This paper describes digital image histogram modification using a discrete raster and quantized gray levels. We let the histogram of an original picture be p, and first process it toward an aim histogram pi, The gray level transformation and resulting histogram qkf can be decided by Eqs. (2) and (3). We explain the effect of histogram modification by a theorem. In accordance with the visual character of the eyes, we select an appropriate aim histogram p;. If p, is constant, p; may be represented by a beta distribution which can be varied by altering the parameters a and /3. We determine the optimum quantization gray levels for different visual models. We change the histogramp, by an order-preserving and layer-preserving gray level transform which has layers at the optimum quantization levels. This may be a simpler and more effective way of histogram modification. Finally, we introduce the concept of apparent entropy of au image, and suggest an approximation method of calculation of apparent entropy. Application
of the One-Dimemional
Fourier
Tnamfotm
for
Tracking
Moving
Objects
in Noby
EmGrmmentJ:
SARAH A. RAJALA, ALFY N. RIDDLE, AND WESLEY E. SNYDER. North Carolina State University. Electrical Engineering Department, Box 5275, Raleigh, North Carolina 27650. Received March I, 1982: revised July 20, 1982. In [ 11, an algorithm was presented which operates on an image sequence to identify all sets of pixels having the same velocity. The algorithm operates by performing a transformation in which all pixels witb the same two-dimensional velocity map to a peak in a transform space. The transform can be decomposed into application of the one-dimensional Fourier transform and therefore can gain from the computational advantages of the FFT. This paper is concerned with the ftmdamental limitations of that algorithm, particularly as relates to its sensitivity to image-disturbing parameters as noise, jitter, and clutter. A modification to the algorithm is then proposed which increases its robustness in the presence of these disturbances.
OF
PAPERS
ACCEPTED
FOR
PUBLICATION
197
A Spatio-Temporal Gradient Method for Estimating the Dkptbcement Field in Time- Varying Imagery. R. PAQUIN AND E. DUBOIS. INRS-Telecommunications, 3 Place du Commerce, Ile des Soeurs, Quebec, Canada, H3E 1H6. Received February 18, 1982; revised July 16, 1982. The displacement between successive frames of each picture element in an image sequence forms a two-dimensional vector field called the displacement field (or optical flow). This paper presents an algorithm for estimating the displacement field, based on a constraint equation relating the spatial gradient to a temporal directional derivative for a moving object. The estimate for a given picture element is obtained by updating the estimate for the corresponding picture element in the previous frame, using information in a three-dimensional block centered on the picture element of interest. The performance of this estimator has been tested on a number of sequences of real imagery, both with artificial displacements and with natural motion, and the main parameters of the estimator have been optimized. It has been found to be accurate, and robust in the presence of noise. A number of simplifications to reduce the computational complexity of the algorithm have been proposed, and their effects on performance have been studied.
Unakstanding Blood Cell Motion. MARTIN D. LEVINE AND YOUSSRY and Graphics Laboratory, Department of Electrical Engineering. Dentistry, McGill University, Montreal, Quebec, Canada. Received 1982.
M. YOUSSEF. Computer Vision PETER B. NOBLE, Faculty of March 1, 1982; revised July 7,
The main function of the surface of a blood cell is to receive information from the environment. Experiments have indicated that the cell membrane plays a vital role in the life, development, and regulation of cells. However, there is no existing method to quantify the observable changes in membrane shape that occur in locomotion. The main goal of this research is to develop an image interpretation system capable of analyzing the structural changes in the morphology of cells from a sequence of pictures, using automatic techniques of image processing. A model for a general dynamic scene analysis system is described. It consists of three basic entities: dynamic data, static data, and a collection of analysis processes. Based on this model, we have implemented a rule-based image interpretation system for moving cells. The system consists of different cooperating computational processes, which interact with two common memories, a short term memory (STM) and a long term memory (LTM). The STM contains a dynamic record of the instantaneous cell motion, shape, and structural changes, as well as the current global description of the cell behaviour. The LTM data are static and are implemented as rules. These describe the general model of the morphology of the cells under analysis, as well as control information pertinent to the computational processes. The latter are activated by the control rules throughout the three hierarchical analysis stages: static, incremental and global. They interact through the STM using the information stored in the LTM, until a complete description of the dynamic cell motion and morphology is obtained. The system has been successfully employed to analyze and study the pseudopod kinetics of white blood cells.
S. N. JAYARAMAMLJRTHY AND RAMESH An Approach to the Segmentation of Textured Dynamic Scenes. JAIN. Intelligent Systems Laboratory, Department of Computer Science, Wayne State University, Detroit, Michigan 48202. Received March 8, 1982; revised July 20, 1982. This moving regions used to and the illustrate indicator
paper presents an approach for the segmentation of dynamic scenes containing textured objects against a textured background. This multistage approach first uses differencing to obtain active in the frame which contain moving objects. In the next stage, a Hough transform technique is determine the motion parameters associated with each active region. Finally, the intensity changes motion parameters are combined to obtain the masks of the moving objects. Our experiments the efficacy of the approach for moving textured objects even in the presence of occlusion. An that signals the presence of the rotational component of the object motion can also be extracted.
ALAN E. COWART. Research Triangle The Detection of Unresohwd Targets Using the Hough Transform. Institute, North Carolina State University, Raleigh, North Carolina 27650. WESLEY E. SNYDER. W. HOWARD RUEDGER. Rese‘arch North Carolina State University, Raleigh, North Carolina 27650. Triangle Institute. Received March 8, 1982; revised July 21, 1982.
Clutter resulting from drift and vibration in a sensor’s line-of-sight and time-varying components in the background can seriously hinder the detection of faint, unresolved (i.e., point) targets moving against a background. However, these targets produce well-defined patterns of motion referred to as tracks whereas the effects of noise and clutter are more random. Frame-to-frame differencing can be used to reject clutter and enhance the detection of moving targets. These difference frames can then be combined recursively to form target tracks. The tracks of nonmaneuvering (i.e., constant velocity) targets appear as line segments that can be detected using the Hough transform. In addition, the current position and heading of a target can be determined using a technique based on matched filtering. An example demonstrating the performance of this technique is also presented. On Sequential and Pardel Node-Rewithg Grrcgrl, Gmnnasrs, II. D. JANSENS AND R. VERRAEDT. Department of Mathematics, U.I.A., University of Antwerp, B-2610 Wilrijk, Belgium. Cr. ROZEN~ERG. Institute of Applied Mathematics and Computer Science, University of Leiden, The Netherlands. Received July 12, 1982. This paper directly continues research initiated in Computer Graphics and Image Processing, 18 (19823. Several new aspects of the relationship between a comection relation mechanism and a stencil mechanism used for specifying embeddings in graph grammars are considered. NOTES and Metho& of H&gram Modification Aabpted for V&al Perception Fu - NIAN Ku. Shanghai Jiao Tong University, Shanghai, China Received July 6, 1981; revised January 22 and July 12, 1982.
The Principks
This paper describes digital image histogram modification using a discrete raster and quantized gray levels. We let the histogram of an original picture be p, and first process it toward an aim histogram pi, The gray level transformation and resulting histogram qkf can be decided by Eqs. (2) and (3). We explain the effect of histogram modification by a theorem. In accordance with the visual character of the eyes, we select an appropriate aim histogram p;. If p, is constant, p; may be represented by a beta distribution which can be varied by altering the parameters a and /3. We determine the optimum quantization gray levels for different visual models. We change the histogramp, by an order-preserving and layer-preserving gray level transform which has layers at the optimum quantization levels. This may be a simpler and more effective way of histogram modification. Finally, we introduce the concept of apparent entropy of au image, and suggest an approximation method of calculation of apparent entropy. Application
of the One-Dimemional
Fourier
Tnamfotm
for
Tracking
Moving
Objects
in Noby
EmGrmmentJ:
SARAH A. RAJALA, ALFY N. RIDDLE, AND WESLEY E. SNYDER. North Carolina State University. Electrical Engineering Department, Box 5275, Raleigh, North Carolina 27650. Received March I, 1982: revised July 20, 1982. In [ 11, an algorithm was presented which operates on an image sequence to identify all sets of pixels having the same velocity. The algorithm operates by performing a transformation in which all pixels witb the same two-dimensional velocity map to a peak in a transform space. The transform can be decomposed into application of the one-dimensional Fourier transform and therefore can gain from the computational advantages of the FFT. This paper is concerned with the ftmdamental limitations of that algorithm, particularly as relates to its sensitivity to image-disturbing parameters as noise, jitter, and clutter. A modification to the algorithm is then proposed which increases its robustness in the presence of these disturbances.