{"title":"Two dimensional CAD-based object recognition","authors":"Cho-Huak Teh, R. Chin","doi":"10.1109/ICPR.1988.28249","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28249","url":null,"abstract":"A local feature-aggregation method for recognizing two-dimensional objects based on their CAD models is presented. The method can handle cases in which the objects are translated, rotated, scaled and occluded, and it is well suited for parallel implementation. Two types of local features, the L structures and the U structures, are extracted from the input image and matched with those of a model to search for an object similar to the model. Each of the matches hypothesizes the locations of the object in the input image, and score (similarity measure) is computed and associated with the hypothesized location to indicate the probability of the match. Matches that hypothesize the same location will have the score associated with the location incremented. A cluster of hypothesized locations with high scores indicates the probable existence of the object in the input image.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122909965","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":"3D cuboid scene understanding by a mixed cognitive graph and log-complex mapping paradigm","authors":"O. Hilsenrath, Y. Zeevi","doi":"10.1109/ICPR.1988.28331","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28331","url":null,"abstract":"A methodology is presented for analysis of wire patterns reduced from scenes containing cuboid objects. The 2D wire-pattern graph is partitioned into subgraphs representing individual cuboids. These are in turn mapped onto the log-complex plane to determine by a simple procedure the 3D orientation of each object. The transform from the polar to the log-complex plane is based on a model of the retinotopic mapping which takes place at the level of the visual cortex, which achieves size-and-rotation invariance.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126267668","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":"Online recognition of free-format Japanese handwritings","authors":"H. Murase","doi":"10.1109/ICPR.1988.28462","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28462","url":null,"abstract":"An online recognition method, called the candidate lattice method, is described for free-format written Japanese character strings, which may contain characters with separated constituents or overlapping characters. The method conducts segmentation and recognition of individual character-candidates, and applies linguistic information to determine the most probable character string to achieve high recognition rates. Special hardware designed to realize a real-time recognition system is also introduced. The method, used on special hardware, attained a segmentation rate of 98.8% and an overall recognition rate of 98.7% for 105 samples.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125776031","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}
Tian-You Gu, Bao-Yong Wu, C. Zhang, Dian-Cheng Zhang
{"title":"An experimental system for the waveform recognition of impedance plethysmography","authors":"Tian-You Gu, Bao-Yong Wu, C. Zhang, Dian-Cheng Zhang","doi":"10.1109/ICPR.1988.28270","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28270","url":null,"abstract":"An impedance waveform recognition system is developed which can perform both cardiac and pulmonary waveform recognition in a single system. The basic structure of the system is outlined, with special attention to the recognition of the four physiological signals: electrocardiogram, dz/dt, Delta Z, and phonocardiogram. Good agreement has been between measurements made by the system and by doctors.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130558140","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. Chianese, L. Cordella, M. D. Santo, A. Marcelli, M. Vento
{"title":"A preliminary approach to the design and evaluation of a reconfigurable architecture for computer vision","authors":"A. Chianese, L. Cordella, M. D. Santo, A. Marcelli, M. Vento","doi":"10.1109/ICPR.1988.28340","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28340","url":null,"abstract":"An analytical model describing the performance of a mesh-connected array of state-of-the-art VLSI microprocessors embedded in a CSP-like environment, is presented. The mode has been developed in the framework of a study aimed at the design and evaluation of a reconfigurable architecture especially suitable for the execution of both low and high level vision tasks. The validity of the model is demonstrated and its use illustrated.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"625 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116202864","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":"Partial matching of two dimensional shapes using random coding","authors":"Chin-Hwa Lee, Gim Pew Quek","doi":"10.1109/ICPR.1988.28173","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28173","url":null,"abstract":"Three algorithms for coding the boundary of two-dimensional shapes are described. In each algorithm, each boundary point is coded with respect to another point picked at random from the boundary. Using this method, an effective and efficient correlation technique to match two-dimensional shapes is developed. This technique can be used to match shapes of arbitrary scale and orientation. The given shape can have a closed or open boundary or even have a portion obstructed from the view. Matching can be performed with varying degrees of detail, giving the technique an added robustness, against geometrical distortions. It can also discriminate between different shapes. On an IBM 3033 computer it typically takes 10 CPU-seconds to generate one correlation curve between two shapes, each with a 500-point boundary curve.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121223055","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":"Semi-continuous hidden Markov models in isolated word recognition","authors":"X. Huang, M. Jack","doi":"10.1109/ICPR.1988.28254","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28254","url":null,"abstract":"A semicontinuous hidden Markov model is proposed to incorporate the vector quantization distortion into the general hidden Markov model methodology under a probabilistic framework. It provides a relatively simple but powerful tool for modeling time-varying signal sources. Experimental results show that the recognition accuracy of the semi-continuous model is measurably improved in comparison to that of the conventional discrete hidden Markov model and template-based dynamic time warping techniques.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126791871","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":"Multi-layer projections for the classification of similar Chinese characters","authors":"Kai Wang, Y. Tang, C. Suen","doi":"10.1109/ICPR.1988.28376","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28376","url":null,"abstract":"An algorithm is presented of extracting features from Chinese characters. These features consist of the Fourier spectrum of projections obtained from multiple-layers of annular partitions. This method takes into consideration the square shape of Chinese characters to that the extracted features contain the significant information of the different parts of the character, and are insensitive to rotation and linear displacement. For the experiments, 97 similar Chinese characters were selected from the most frequently used characters. These characters were divided into 34 groups according to similarity in shape. Three different fonts of Chinese characters (Song, Kai and Bold face) were used. Four additional symbols were also included to study the effects of character symmetry on the proposed algorithm. Experimental results indicate that for any displacement and for rotations in the range of (-180 degrees , +180 degrees ), this method can separate without exception all similar Chinese characters including the complex ones.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123815547","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 segmentation and object extraction algorithm with linear memory and time constraints","authors":"R. S. Anbalagan, G. Hu, Anil K. Jain","doi":"10.1109/ICPR.1988.28302","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28302","url":null,"abstract":"An experimental segmentation and object extraction algorithm is described. The system was developed for medical image processing with the primary application being DNA (deoxyribonucleic acid) sequencing. A typical DNA sequencing can involve processing the image of an autodiagram of size 14*17 inches resulting in a 2048*8600 digitized image under the specified spatial resolutions. The digitized image is too big to manage, even using super-minicomputers such as DEC VAX 11/780, and to perform any amount of classical image processing. Therefore, an elegant hardware and software design is necessary to deal with the large image and to complete the image-understanding task in an efficient manner. This work focuses on the image-processing aspects of the system and describes the run-length image representation, a link list data structure, a heuristic connected component analysis algorithm based on the data structure, a primitive object segmentation algorithm, and feature extraction.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132761869","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 nonparametric approach to linear feature extraction; application to classification of binary synthetic textures","authors":"A. Hillion, P. Masson, C. Roux","doi":"10.1109/ICPR.1988.28433","DOIUrl":"https://doi.org/10.1109/ICPR.1988.28433","url":null,"abstract":"A nonparametric approach to linear feature extraction is presented. The theoretical background is introduced with a derivation of the equation that gives the best scalar extractor according to Patrick-Fischer distance. The outlines of the implementation are given. The method is applied to the classification of binary synthetic textures with natural visual aspect. The performances of the proposed method are shown to be better than the Fisher discriminant-analysis-based classifier. Concluding remarks are given for future improvements, further applications, and theoretical discussion.<<ETX>>","PeriodicalId":314236,"journal":{"name":"[1988 Proceedings] 9th International Conference on Pattern Recognition","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1988-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133527696","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}