G. Bellaire, K. Talmi, E. Oezguer, A. Koschan, Robert-Rössle Klinik
{"title":"Object recognition: obtaining 2-D reconstructions from color edges","authors":"G. Bellaire, K. Talmi, E. Oezguer, A. Koschan, Robert-Rössle Klinik","doi":"10.1109/IAI.1998.666884","DOIUrl":"https://doi.org/10.1109/IAI.1998.666884","url":null,"abstract":"This article presents a complete hybrid object recognition system for three-dimensional objects using characteristic views (ChVs). High-quality 2-D reconstructions have to be generated from intensity or color data, respectively, to integrate the ChV representation method into a recognition system. First, we present an approach for obtaining edges and gradient information from color images. Second, we present an adaptive edge linking process that transforms the image data into a suitable form. The edge linker uses an energy function to combine data from the edge detector and color gradient information to improve the results of the edge detector for the 2-D reconstruction. Results are presented for real color images.","PeriodicalId":373701,"journal":{"name":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131301674","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":"A robust registration technique for multi-sensor images","authors":"G. Zamora, M. Dickens, S. Mitra","doi":"10.1109/IAI.1998.666865","DOIUrl":"https://doi.org/10.1109/IAI.1998.666865","url":null,"abstract":"This paper describes an improved technique to register multi-sensor images by segmenting the images by adaptive clustering prior to performing preprocessing and cepstrum operation to determine the translational displacement. The difficulty in registering multi sensor images lies in the fact that the images of the same scene acquired by different sensors often appear different in detailed structures. Therefore the common features existing in such images need to be identified by suitable preprocessing operations for the success of the cepstral registration technique. Experimental results demonstrate the feasibility of successful cepstral registration of SAR and electro-optic images of the same scene despite apparent noticeable differences in some embedded structures thus providing a potential powerful tool for automated registration.","PeriodicalId":373701,"journal":{"name":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131115417","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":"Document segmentation using texture variance and low resolution images","authors":"M. Murguia","doi":"10.1109/IAI.1998.666879","DOIUrl":"https://doi.org/10.1109/IAI.1998.666879","url":null,"abstract":"This paper describes a document segmentation method based on segmentation by texture using low resolution gray level images. The method is derived from the human vision perception theory. The concepts used from this theory are, global to local processing and low resolution information. If a document is viewed at a certain distance far from a person, the person sees a blurred image of the document, but is still able to detect the different blocks of the document. Detection is possible since each block has a specific texture pattern. These patterns correspond to regions of text, regions of graphics and regions of pictures. Thus the theory to prove is that a document image can be segmented into regions of text, and regions of graphics and/or pictures using the texture of low resolution images. The method presented in this paper, despite its simplicity, has shown to be effective and robust. It was designed to work with free format documents, text in background other than white, skew greater than 10 degrees. It requires less computation than the segmentation methods using texture described in other papers.","PeriodicalId":373701,"journal":{"name":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133854177","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":"Probabilistic matching for face recognition","authors":"B. Moghaddam, A. Pentland","doi":"10.1109/IAI.1998.666883","DOIUrl":"https://doi.org/10.1109/IAI.1998.666883","url":null,"abstract":"We propose a new technique for direct visual matching of images for the purposes of face recognition, database search and image retrieval. Specifically, we argue in favor of a probabilistic measure of similarity, in contrast to simpler methods which are based on standard L/sub 2/ norms (e.g., template matching) or subspace-restricted norms (e.g., eigenspace matching). The proposed similarity measure is based on a Bayesian analysis using two mutually-exclusive classes of image variation as encountered in a typical face recognition task. The high-dimensional probability density functions for each respective class are obtained from training data using an eigenspace density estimation technique and subsequently used to compute a similarity measure based on the relevant a posteriori probability, which is used to rank matches in the database. The performance advantage of this probabilistic matching technique over standard nearest-neighbor eigenspace matching is demonstrated using results from ARPA's 1996 \"FERET\" face recognition competition, in which this algorithm was found to be the top performer by a 10% (or better) margin to the other competitors.","PeriodicalId":373701,"journal":{"name":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","volume":"325 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133042656","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":"Microcalcification cluster detection in digitized mammograms using multiscale techniques","authors":"H. Choe, A. Chan","doi":"10.1109/IAI.1998.666854","DOIUrl":"https://doi.org/10.1109/IAI.1998.666854","url":null,"abstract":"The introduction of multiscale techniques to signal and image processing has provided a new tool to create innovative methods for solving problems in the areas of data compression, signal analysis, and noise removal. Although these techniques are popular and used extensively in research and in engineering applications, their use in signature detection and classification is still an area open to extensive investigation. This paper discusses multiscale techniques working in synergy with other processing techniques to detect and recognize abnormal and cueing signatures that are important to diagnostic medicine-detection and recognition of microcalcification clusters in mammograms. In this application, an innovative detection algorithm that takes advantage of multiresolution analysis and synthesis is developed to assist radiologists looking for clusters of microcalcifications in digitized mammograms. The algorithm presented in this paper successfully limits the false positives. An algorithm description and examples are shown in this paper.","PeriodicalId":373701,"journal":{"name":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117063212","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":"Handwritten digit recognition using combination of neural network classifiers","authors":"A. Khofanzad, C. Chung","doi":"10.1109/IAI.1998.666880","DOIUrl":"https://doi.org/10.1109/IAI.1998.666880","url":null,"abstract":"A new classification scheme for handwritten digit recognition is proposed. The method is based on combining the decisions of two multilayer perceptron (MLP) artificial neural network classifiers operating on two different feature types. The first feature set is defined on the pseudo Zernike moments of the image whereas the second feature type is derived from the shadow code of the image using a newly defined projection mask. A MLP network is employed to perform the combination task. The performance is tested on a data base of 15000 samples and the advantage of the combination approach is demonstrated.","PeriodicalId":373701,"journal":{"name":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123528859","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}