An image comparison algorithm employing a new notion of match consistency has been developed for the application of mutation detection on images of two-dimensional electrophoretic gels. The application requires a very high degree of accuracy in image comparison due to the rareness of mutation. The image comparison algorithm achieves high accuracy through monitoring, isolating and diagnosing inconsistencies in the matching process. The methodology is based on algorithms for monitoring symmetry relations between match hypothesis made during the course of processing. Algorithms are given which explore violations of the basic symmetry relation. Diagnostic procedures partition symmetry violations into classes that are identified with the failure of certain essential heuristics within the comparison algorithm. This methodology provides the basis for understanding and overcoming the limitations of these heuristics in order to achieve higher accuracy.<>
{"title":"A new methodology for isolating and diagnosing inconsistencies in image matching, as applied to the analysis of 2-D electrophoretic gels","authors":"G. Markovich, M. Skolnick, M. Core","doi":"10.1109/ACV.1992.240311","DOIUrl":"https://doi.org/10.1109/ACV.1992.240311","url":null,"abstract":"An image comparison algorithm employing a new notion of match consistency has been developed for the application of mutation detection on images of two-dimensional electrophoretic gels. The application requires a very high degree of accuracy in image comparison due to the rareness of mutation. The image comparison algorithm achieves high accuracy through monitoring, isolating and diagnosing inconsistencies in the matching process. The methodology is based on algorithms for monitoring symmetry relations between match hypothesis made during the course of processing. Algorithms are given which explore violations of the basic symmetry relation. Diagnostic procedures partition symmetry violations into classes that are identified with the failure of certain essential heuristics within the comparison algorithm. This methodology provides the basis for understanding and overcoming the limitations of these heuristics in order to achieve higher accuracy.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116505262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multiscale Analysis of surfaces allows a hierarchical representation of their composing features. To represent a surface at a given scale, structures that are insignificant at that scale have to be eliminated. A typical example for this approach is cartography. However, the aims of cartographers reach beyond simply gradually eliminating the structures; in the majority of cases, the nature of geomorphological structures which compose the surface have to be preserved across all scales. Thus a global smoothing of the surface is not suitable to solve the present problem, since that would cause inevitably morphological modifications of certain important structures. In fact, the points to be preserved across scale variations are to be chosen interactively by the user. The authors present a surface model which allows them to perform a Multiscale Analysis which takes the importance of local structures into consideration, i.e. structures which are inherent to the relief morphology. From that discrete model we extract a context-dependent Multiscale Analysis Operator which can be isotropic or anisotropic and can be expressed in different forms.<>
{"title":"A multiscale analysis model applied to natural surfaces","authors":"F. Falzon, G. Giraudon, M. Berthod","doi":"10.1109/ACV.1992.240317","DOIUrl":"https://doi.org/10.1109/ACV.1992.240317","url":null,"abstract":"Multiscale Analysis of surfaces allows a hierarchical representation of their composing features. To represent a surface at a given scale, structures that are insignificant at that scale have to be eliminated. A typical example for this approach is cartography. However, the aims of cartographers reach beyond simply gradually eliminating the structures; in the majority of cases, the nature of geomorphological structures which compose the surface have to be preserved across all scales. Thus a global smoothing of the surface is not suitable to solve the present problem, since that would cause inevitably morphological modifications of certain important structures. In fact, the points to be preserved across scale variations are to be chosen interactively by the user. The authors present a surface model which allows them to perform a Multiscale Analysis which takes the importance of local structures into consideration, i.e. structures which are inherent to the relief morphology. From that discrete model we extract a context-dependent Multiscale Analysis Operator which can be isotropic or anisotropic and can be expressed in different forms.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133494914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The B-spline stands as one of the most efficient curve (surface) representation, and possesses very attractive properties such as spatial uniqueness, boundedness and continuity, local shape controllability, and invariance to affine transformations. These properties made them very attractive for curve representation in computer aided design and computer graphics. Very little work, however, has been devoted to them for recognition purpose. One possible reason might be due to the fact that the B-spline curve is not uniquely described by a single set of control points, which make the curve matching (recognition) process not a simple comparison between the respective parameters of the curves to be matched. The paper is an attempt to find matching solutions despite this limitation and addresses the problems of invariant matching and classification of 2D closed curves with application in identification of aircraft types based on image silhouettes, and writer-identification based on hand written text.<>
{"title":"Curve recognition using B-spline representation","authors":"F. Cohen, Zhaohui Huang, Zhengwei Yang","doi":"10.1109/ACV.1992.240308","DOIUrl":"https://doi.org/10.1109/ACV.1992.240308","url":null,"abstract":"The B-spline stands as one of the most efficient curve (surface) representation, and possesses very attractive properties such as spatial uniqueness, boundedness and continuity, local shape controllability, and invariance to affine transformations. These properties made them very attractive for curve representation in computer aided design and computer graphics. Very little work, however, has been devoted to them for recognition purpose. One possible reason might be due to the fact that the B-spline curve is not uniquely described by a single set of control points, which make the curve matching (recognition) process not a simple comparison between the respective parameters of the curves to be matched. The paper is an attempt to find matching solutions despite this limitation and addresses the problems of invariant matching and classification of 2D closed curves with application in identification of aircraft types based on image silhouettes, and writer-identification based on hand written text.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115083435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Model-based vision techniques, originally developed for the recognition and pose recovery of vehicles in a single image, are used here to track vehicles through a sequence of images. Knowledge of the position of the camera with respect to the ground plane is used to reduce the search space of possible vehicle positions from six dimensions to three. The expected dynamics of vehicles are expressed in a Kalman filter, which predicts the likely poses in successive frames and provides a smoothed description of the vehicles' motion. The notion of equivalence classes defined by a search of the parameter space is developed as an indicator of the performance of the pose-refinement sub-system. The system is illustrated and assessed by using the size of the correct class as a performance measure.<>
{"title":"Performance assessment of model-based tracking","authors":"K. Baker, G. Sullivan","doi":"10.1109/ACV.1992.240330","DOIUrl":"https://doi.org/10.1109/ACV.1992.240330","url":null,"abstract":"Model-based vision techniques, originally developed for the recognition and pose recovery of vehicles in a single image, are used here to track vehicles through a sequence of images. Knowledge of the position of the camera with respect to the ground plane is used to reduce the search space of possible vehicle positions from six dimensions to three. The expected dynamics of vehicles are expressed in a Kalman filter, which predicts the likely poses in successive frames and provides a smoothed description of the vehicles' motion. The notion of equivalence classes defined by a search of the parameter space is developed as an indicator of the performance of the pose-refinement sub-system. The system is illustrated and assessed by using the size of the correct class as a performance measure.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133850558","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. R. Rao, N. Ramesh, F. Y. Wu, J. Mandeville, P. Kerstens
Confocal imaging is an emerging technique for the measurement of surface topography in inspection. The authors present a system designed for fast acquisition and processing of confocal images, which consists of an optical front end using tilted confocal scanning, and an image processing module. The function of the image processing module is to improve signal resolution, perform smoothing and detect surfaces in the incoming signal. The input signal is first deconvolved in order to improve the depth resolution, and then processed to identify significant peaks. These peaks represent the position of different surfaces in the object being inspected. These peak locations are smoothed using a cluster based smoothing scheme to combat noise. For semi-transparent materials, the authors system is capable of detecting up to two surfaces at a given location.<>
{"title":"Algorithms for a fast confocal optical inspection system","authors":"A. R. Rao, N. Ramesh, F. Y. Wu, J. Mandeville, P. Kerstens","doi":"10.1109/ACV.1992.240299","DOIUrl":"https://doi.org/10.1109/ACV.1992.240299","url":null,"abstract":"Confocal imaging is an emerging technique for the measurement of surface topography in inspection. The authors present a system designed for fast acquisition and processing of confocal images, which consists of an optical front end using tilted confocal scanning, and an image processing module. The function of the image processing module is to improve signal resolution, perform smoothing and detect surfaces in the incoming signal. The input signal is first deconvolved in order to improve the depth resolution, and then processed to identify significant peaks. These peaks represent the position of different surfaces in the object being inspected. These peak locations are smoothed using a cluster based smoothing scheme to combat noise. For semi-transparent materials, the authors system is capable of detecting up to two surfaces at a given location.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114053787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
CARTRACK is a computer vision system that can reliably detect, track, and measure vehicle rears in images from a video camera in a following car. The system exploits the symmetry property typical for the rear of most vehicles on normal roads. The authors present two novel methods for detecting mirror symmetry in images, one based directly on the intensity values and another one based on a discrete representation of local orientation. CARTRACK has been used for realtime experiments with test vehicles of Volkswagen and Daimler-Benz.<>
{"title":"CARTRACK: computer vision-based car following","authors":"Thomas Zielke, M. Brauckmann, W. Seelen","doi":"10.1109/ACV.1992.240316","DOIUrl":"https://doi.org/10.1109/ACV.1992.240316","url":null,"abstract":"CARTRACK is a computer vision system that can reliably detect, track, and measure vehicle rears in images from a video camera in a following car. The system exploits the symmetry property typical for the rear of most vehicles on normal roads. The authors present two novel methods for detecting mirror symmetry in images, one based directly on the intensity values and another one based on a discrete representation of local orientation. CARTRACK has been used for realtime experiments with test vehicles of Volkswagen and Daimler-Benz.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122838677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Presents a robotic video telephone application of the Cortex-1 miniaturized space-variant active vision system. The embedded processor architecture of Cortex-1 enables it to implement a variety of functions not found in conventional video telephones, for example the camera tracks moving users with its pantilt mechanism. The authors also report an analog channel coding scheme to transmit logmap video images through band-limited analog channels such as the public switched telephone network (PSTN). The transmitter divides the frequency band into 768 channels, and modulates two values in quadrature on each channel. Some channels are reserved for special calibration signals enabling the receiver to recover both the phase and magnitude of the transmitted signal. The remaining channels carry pixel intensities.<>
{"title":"Voice-bandwidth visual communication through logmaps: the Telecortex","authors":"R. Wallace, B. Bederson, E. Schwartz","doi":"10.1109/ACV.1992.240333","DOIUrl":"https://doi.org/10.1109/ACV.1992.240333","url":null,"abstract":"Presents a robotic video telephone application of the Cortex-1 miniaturized space-variant active vision system. The embedded processor architecture of Cortex-1 enables it to implement a variety of functions not found in conventional video telephones, for example the camera tracks moving users with its pantilt mechanism. The authors also report an analog channel coding scheme to transmit logmap video images through band-limited analog channels such as the public switched telephone network (PSTN). The transmitter divides the frequency band into 768 channels, and modulates two values in quadrature on each channel. Some channels are reserved for special calibration signals enabling the receiver to recover both the phase and magnitude of the transmitted signal. The remaining channels carry pixel intensities.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129775766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Describes a new method of tracking targets across a sequence of images and estimating the range of these tracked objects from the camera. The motion of the camera between the successive frames is assumed to be known. The distance from the sensor to the objects is assumed to be much larger than the physical dimensions of the object. the approach presented makes use of the known sensor motion to generate expected images which are then used in establishing a reliable correspondence and in tracking the targets across the image sequence. A mean normalized area correlation method is used to establish the inter-frame correspondence. Once this correspondence is established, two new methods of estimating the range of the target from the sensor are also developed. The techniques developed are tested with good success rate on a sequence of real aerial images.<>
{"title":"Target tracking and range estimation using an image sequence","authors":"R. Talluri, W. Choate","doi":"10.1109/ACV.1992.240324","DOIUrl":"https://doi.org/10.1109/ACV.1992.240324","url":null,"abstract":"Describes a new method of tracking targets across a sequence of images and estimating the range of these tracked objects from the camera. The motion of the camera between the successive frames is assumed to be known. The distance from the sensor to the objects is assumed to be much larger than the physical dimensions of the object. the approach presented makes use of the known sensor motion to generate expected images which are then used in establishing a reliable correspondence and in tracking the targets across the image sequence. A mean normalized area correlation method is used to establish the inter-frame correspondence. Once this correspondence is established, two new methods of estimating the range of the target from the sensor are also developed. The techniques developed are tested with good success rate on a sequence of real aerial images.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126194099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A method for the recognition of multifont printed characters is proposed, giving emphasis to the identification of structural descriptions of character shapes using prototypes. Noise and shape variations are modeled as series of transformations from groups of features in the data to features in each prototype. Thus, the method manages systematically the relative distortion between a candidate shape and its prototype, accomplishing robustness to noise with less than two prototypes per class, on the average. Our method uses a flexible matching between components and a flexible grouping of the individual components to be matched. A number of shape transformations are defined. Also, a measure of the amount of distortion that these transformations cause is given. The problem of classification of character shapes is defined as a problem of optimization among the possible transformations that map an input shape into prototypical shapes. Some tests with hand printed numerals confirmed the method's high robustness level.<>
{"title":"A shape analysis model with applications to a character recognition system","authors":"J. Rocha, T. Pavlidis","doi":"10.1109/ACV.1992.240313","DOIUrl":"https://doi.org/10.1109/ACV.1992.240313","url":null,"abstract":"A method for the recognition of multifont printed characters is proposed, giving emphasis to the identification of structural descriptions of character shapes using prototypes. Noise and shape variations are modeled as series of transformations from groups of features in the data to features in each prototype. Thus, the method manages systematically the relative distortion between a candidate shape and its prototype, accomplishing robustness to noise with less than two prototypes per class, on the average. Our method uses a flexible matching between components and a flexible grouping of the individual components to be matched. A number of shape transformations are defined. Also, a measure of the amount of distortion that these transformations cause is given. The problem of classification of character shapes is defined as a problem of optimization among the possible transformations that map an input shape into prototypical shapes. Some tests with hand printed numerals confirmed the method's high robustness level.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127254918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A self-reference technique is developed for detecting the location of defects in repeated pattern wafers and masks. The application area of the proposed method includes inspection of memory chips, shift registers, switch capacitors, and CCD arrays. Using high resolution spectral estimation algorithms, the proposed technique first extracts the period and structure of repeated patterns from the image to sub-pixel resolution, and then produces a defect-free reference image for making comparison with the actual image. Since the technique acquires all its needed information from a single image, there is no need for a database image, a scaling procedure, or any a-priori knowledge about the repetition period of the patterns.<>
{"title":"Automated direct patterned wafer inspection","authors":"B. Khalaj, H. Aghajan, T. Kailath","doi":"10.1109/ACV.1992.240303","DOIUrl":"https://doi.org/10.1109/ACV.1992.240303","url":null,"abstract":"A self-reference technique is developed for detecting the location of defects in repeated pattern wafers and masks. The application area of the proposed method includes inspection of memory chips, shift registers, switch capacitors, and CCD arrays. Using high resolution spectral estimation algorithms, the proposed technique first extracts the period and structure of repeated patterns from the image to sub-pixel resolution, and then produces a defect-free reference image for making comparison with the actual image. Since the technique acquires all its needed information from a single image, there is no need for a database image, a scaling procedure, or any a-priori knowledge about the repetition period of the patterns.<<ETX>>","PeriodicalId":153393,"journal":{"name":"[1992] Proceedings IEEE Workshop on Applications of Computer Vision","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1992-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127982038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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