{"title":"A practical obstacle detection and avoidance system","authors":"Sumit Badal, S. Ravela, B. Draper, A. Hanson","doi":"10.1109/ACV.1994.341294","DOIUrl":"https://doi.org/10.1109/ACV.1994.341294","url":null,"abstract":"A practical real-time system for passive obstacle detection and avoidance is presented. Range information is obtained from stereo images by first computing a disparity picture from the image pair and extracting points above the ground plane. Then these points are projected onto the ground plane and an Instantaneous Obstacle Map (IOM) is obtained. The IOM is transformed into a one dimensional steering vector that represents the hindrance associated with steering in a particular direction and then a one dimensional search is performed on the steering vector for an angle with least hindrance. The steering direction and hindrance value are used to set the speed of the vehicle. This system has been implemented on the Mobile Perception Lab (MPL) at University of Massachusetts at Amherst with considerable success, running at 2 Hz for 256/spl times/240 sized images.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125732232","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}
{"title":"Using modeling and fuzzy logic to detect and track microvessels in conjunctiva images","authors":"C. Wick, M. Loew, J. Kurantsin-Mills","doi":"10.1109/ACV.1994.341297","DOIUrl":"https://doi.org/10.1109/ACV.1994.341297","url":null,"abstract":"The conjunctiva is a thin membrane that covers the surface of the eye and reveals the small blood vessels of the microcirculation for detailed non-invasive study. The morphology of these vessels is of interest because structural changes in the vascular bed have been shown to occur coincident with certain diseases. Detecting these changes could be used as an early indication, leading to more timely treatment. Our efforts have been to find a reliable method to automate the currently manual methods of analyzing images of the conjunctiva. Our approach has been to first model the illumination/reflection processes that contribute to a scene. We have then used the products of this model to develop some algorithms based on fuzzy logic to reliably detect blood vessel pixels in actual conjunctiva images. Work is progressing in the use of fuzzy logic concepts to track vessels from these detected points so as to provide complete vessel paths and other morphological information.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126325095","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}
{"title":"Compilation of mosaics from separately scanned line drawings","authors":"R. D. T. Janssen, A. Vossepoel","doi":"10.1109/ACV.1994.341286","DOIUrl":"https://doi.org/10.1109/ACV.1994.341286","url":null,"abstract":"In automatic line drawing interpretation (e.g. map interpretation), one of the problems encountered is the finite size of scanners, or that scanners of the required size are not available. Often, one large scan is necessary for the interpretation process, instead of several smaller ones generated by the usual scanning in parts. This paper describes a method for automatically compiling mosaics from separately scanned line drawings. A mosaic is a collection of separately obtained images which are combined to form one larger image. The method is based on vectorization of the line drawings, which is used to select the control points for a geometric transformation automatically. It is not necessary to specify the overlap area between the line drawings. The resulting system is evaluated using large scale maps. Experiments with different overlaps between the line drawings were done. Results are good: the algorithm succeeds in finding accurate parameters for the transformation.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133780193","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}
{"title":"Model validation for change detection [machine vision]","authors":"M. Bejanin, A. Huertas, G. Medioni, R. Nevatia","doi":"10.1109/ACV.1994.341304","DOIUrl":"https://doi.org/10.1109/ACV.1994.341304","url":null,"abstract":"An important application of machine vision is to provide a means to monitor a scene over a period of time and report changes in the content of the scene. We have developed a validation mechanism that implements the first step towards a system for detecting changes in images of aerial scenes. By validation we mean the confirmation of the presence of model objects in the image. Our system uses a 3-D site model of the scene as a basis for model validation, and eventually for detecting changes and to update the site model. The scenario for our present validation system consists of adding a new image to a database associated with the site. The validation process is implemented in three steps: registration of the image to the model, or equivalently, determination of the position and orientation of the camera; matching of model features to image features; and validation of the objects in the model. Our system processes the new image monocularly and uses shadows as 3-D clues to help validate the model. The system has been tested using a hand-generated site model and several images of a 500:1 scale model of the site, acquired form several viewpoints.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134560910","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}
{"title":"Model-based path finding using adjacent area shape","authors":"T. Okada, S. Meguro, M. Okudaira","doi":"10.1109/ACV.1994.341321","DOIUrl":"https://doi.org/10.1109/ACV.1994.341321","url":null,"abstract":"This paper describes a robust and broadly applicable path-finding method that uses the range data of object surfaces adjacent to the path. The proposed method locates the path by using the shape defined by multiple sequences of less noisy parts of the range data. It is based on an originally devised algorithm for matching the shape of the object to that of the prototype model. This shape-matching algorithm can define the degree of similarity for curved surfaces three-dimensionally without assuming that the surface consists of parametric surfaces, such as planes, or conic surfaces. Segmentation of the surface is therefore not required. Moreover, this similarity can be defined even if the processing extent is not determined in advance. Consequently, the position of the paths used for robotic movement can be determined accurately from matching information by using less noisy parts of the range data, without putting restrictions on the shape of the object.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124748860","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}
{"title":"Parameterisation of a stochastic model for human face identification","authors":"F. Samaria, A. Harter","doi":"10.1109/ACV.1994.341300","DOIUrl":"https://doi.org/10.1109/ACV.1994.341300","url":null,"abstract":"Recent work on face identification using continuous density Hidden Markov Models (HMMs) has shown that stochastic modelling can be used successfully to encode feature information. When frontal images of faces are sampled using top-bottom scanning, there is a natural order in which the features appear and this can be conveniently modelled using a top-bottom HMM. However, a top-bottom HMM is characterised by different parameters, the choice of which has so far been based on subjective intuition. This paper presents a set of experimental results in which various HMM parameterisations are analysed.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134613485","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}
{"title":"Recognizing a facial image from a police sketch","authors":"Robert G. Uhl, N. Lobo, Y. Kwon","doi":"10.1109/ACV.1994.341299","DOIUrl":"https://doi.org/10.1109/ACV.1994.341299","url":null,"abstract":"This paper presents a theory and practical computations for the recognition of a facial image given a police-artist sketch. First, the facial features of the police sketch are located automatically. Then, regions centered at these positions that contain high intensity variations are temporarily removed. Then a standardization step transforms the sketch image into a \"photograph-like\" image. After this transformation, the high intensity variation regions that were removed are placed back into the standardized image. The resulting image is then passed to the recognition part of our algorithm. In this stage, principle component analysis is performed on both the standardized image to be recognized and the facial images of the training set. Results using actual police sketches and arrest photographs are presented.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"2015 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134040327","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}
Richard P. Wildes, J. Asmuth, Gilbert L. Green, S. Hsu, R. Kolczynski, J. Matey, S. McBride
{"title":"A system for automated iris recognition","authors":"Richard P. Wildes, J. Asmuth, Gilbert L. Green, S. Hsu, R. Kolczynski, J. Matey, S. McBride","doi":"10.1109/ACV.1994.341298","DOIUrl":"https://doi.org/10.1109/ACV.1994.341298","url":null,"abstract":"This paper describes a prototype system for personnel verification based on automated iris recognition. The motivation for this endeavour stems from the observation that the human iris provides a particularly interesting structure on which to base a technology for noninvasive biometric measurement. In particular, it is known in the biomedical community that irises are as distinct as fingerprints or patterns of retinal blood vessels. Further, since the iris is an overt body its appearance is amenable to remote examination with the aid of a computer vision system. The body of this paper details the design and operation of such a system. Also presented are the results of an empirical study where the system exhibits flawless performance in the evaluation of 520 iris images.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"191 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130745263","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}
{"title":"Automatic classification of wooden cabinet doors","authors":"A. L. Abbott, Bin Yuan","doi":"10.1109/ACV.1994.341329","DOIUrl":"https://doi.org/10.1109/ACV.1994.341329","url":null,"abstract":"This paper concerns the use of computer vision techniques for distinguishing finished wooden components in a manufacturing environment. The components are kitchen cabinet doors, which are produced in many different shapes and sizes. We have developed a system which can classify doors quickly and reliably as they travel on a conveyor. Two laser sources are used with three video cameras to obtain profile images. This paper describes the system, the feature extraction process, and the classification method. The system exists as a laboratory prototype, and has been successfully tested with a large number of samples. A duplicate system will be installed in a factory in the near future.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"500 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127033631","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}
T. Hiroi, Shunji Maeda, H. Kubota, Kenji Watanabe, Y. Nakagawa
{"title":"Precise visual inspection for LSI wafer patterns using subpixel image alignment","authors":"T. Hiroi, Shunji Maeda, H. Kubota, Kenji Watanabe, Y. Nakagawa","doi":"10.1109/ACV.1994.341284","DOIUrl":"https://doi.org/10.1109/ACV.1994.341284","url":null,"abstract":"This paper reports on an image processing algorithm and hardware for fast, precise inspection of LSI wafer patterns. In order to detect deep sub-micron defects such as 0.2 /spl mu/m at high speed by grayscale image comparison, we must overcome the sampling errors that inevitably occur between two images during detection. For this purpose, we have developed a subpixel image alignment algorithm that infers the correct sampling position and creates the two resampled images with subpixel accuracy. We have also developed an 8-channel pipelined processor with gate arrays. It has 8/spl times/19,000 gates and can operate at 8/spl times/15 MHz. Evaluation of the system confirmed that the accuracy of the subpixel image alignment was 0.16 pixels or less and that the inspection system could detect 0.18 /spl mu/m defects at a pixel size of 0.25 /spl mu/m for half-micron LSI wafer patterns with an inspection speed of 25 s/cm/sup 2/.<<ETX>>","PeriodicalId":437089,"journal":{"name":"Proceedings of 1994 IEEE Workshop on Applications of Computer Vision","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127668345","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}