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1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Xin, Ying-Jie Zhou, Yuan-Hua Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai China

The paper presents a new theory and method that combines topology and digital image process.ng. It is hopeful for many difficult segmentation problems. Its application for color recognition of geographic maps is also ... 详细信息

ISBN: (纸本)078031865X

关键词： image process.ng

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3D object recognition using qualitative features

3D object recognition using qualitative features

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1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Gu, Siyang Shi, Pengfei Li, Jiegu Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai200030 China

ISBN: (纸本)078031865X

We present a vision system that can be to recognize 3D objects. Surfaces are characterized by surface curvature. Qualitative features are shown to be effective in pruning the search space of possible scene interpretations explored by the recognition and localization technique. Within this paradigm, we implemented a system which extracts planar patches, and patches of quadrics of revolution from a depth map. Reconstructed features are indexed into a model database to verify object hypotheses using the Hough technique. Our approach is surface based and is not sensitive to noise or occlusion. © 1994 IEEE.

关键词： Object recognition

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Fingerprint preclassification using key-points

Fingerprint preclassification using key-points

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1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Shan, Ying Shi, Peng Fei Li, Jie Gu Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai200030 China

ISBN: (纸本)078031865X

A new idea of fingerprint preclassification named the key-point recognition method (KMF) is proposed which only pays attention to whether there is a general feature key-point in a certain area and takes no notice of what the feature is. Using this method, an automatic fingerprint recognition system has been developed, which is characterized by fewer requirements imposed on the preprocess.ng, lower sensitivity to the noise, higher capacity and parallelism being compared with other traditional ones. The system can list out the most promising fingerprints as a preclassifier. © 1994 IEEE.

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Speaker normalization by input space optimization for continuous density hidden Markov models

Speaker normalization by input space optimization for contin...

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1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Wu, Jianxiong Qi, Zeyu Chan, Chorkin Li, Jiegu Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai China Department of Computer Science Universdy of Hong Kong Hong Kong

ISBN: (纸本)078031865X

This paper proposes a novel method of speaker normalization by means of input space optimization for continuous density hidden Markov models (CDHMM). The parameters of a linear feature transformation function are so determined that, together with the previously trained CDHMM parameters, a mis-classification cost function is minimized for the normalizing data set. Preliminary experimental results on the task of sex adaptation for speaker-independent stop consonant discrimination, evaluated from the DARPA TIMIT speech database, demonstrates the effectiveness of the proposed method. © 1994 IEEE.

关键词： Cost functions

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Fingerprint preclassification using key-points

Fingerprint preclassification using key-points

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International Symposium on Speech, image process.ng and Neural Networks

作者： Ying Shan Peng Fei Shi Jie Gu Li Inst. of Image Process. & Pattern Recognition Shanghai Jiaotong Univ. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)078031865X

关键词： Fingerprint recognition Equations Lattices Labeling Supervised learning Energy measurement Frequency measurement Brightness Convergence Hamming distance

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Application constraints in the design of an automatic reading device for analog display instruments

Application constraints in the design of an automatic readin...

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IEEE Workshop on Applications of Computer Vision (WACV)

作者： R. Sablatnig W.G. Kropatsch Dept. of Pattern Recognition & Image Process. Wien Univ. Austria Institute for Automations Department of Pattern Recognition and Image Processing Technical University of of Vienna Vienna Austria

An analysis system design based on experience with a successful application in the field of inspection and calibration of an analog display measuring instrument is presented in this paper. First the measuring instrument is divided into its primitiva, defining the a priori known parameter of the primitiva: shape, relative position and size. According to the shape of the primitiva pattern recognition algorithms are used to detect the primitiva in intensity images. These independent detection algorithms are then grouped into a detecting order with respect to efficiency. Following a discussion of the general design of the detecting algorithm, specific constraints of the application and the industrial environment are considered in order to refine the general design to an applicable and efficient device by modifying both hardware and software configuration depending on the given constraints. Finally, results of the implementation of the algorithm and the constructed image acquisition device are discussed.< >

关键词： Instruments Shape measurement Algorithm design and analysis System analysis and design Inspection Calibration Displays Position measurement Size measurement pattern recognition

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A SYNTHESIS PROCEDURE FOR A GENERALIZEDNEURALNETWORK

A SYNTHESIS PROCEDURE FOR A GENERALIZEDNEURALNETWORK

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1992 International Joint Conference on Neural Networks, IJCNN 1992

作者： Yan, Yan Li, Jie Gu Institute of Image Process and Pattern Recognition Shanghai Jiao Tong University Shanghai200030 China

ISBN: (纸本)0780305590

A FTTB(From Top To Bottom) design strategy for neural network is introduced. From the scheme we present a design method and construct a generalized neural network which has some good qualitative behavior, e.g., ang number of isolated prototypes can be set to asymptotically stable fixpoints, and any track converges to one of the equilibriums. The time/space complexity of our model is O(mn), other than 0(nn) of Hopfield-like models. Simulation experiment shows its good recognition ability. © 1992 IEEE.

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A synthesis procedure for a generalized neural network

A synthesis procedure for a generalized neural network

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International Joint Conference on Neural Networks (IJCNN)

作者： Yan Yan Jie Gu Li Institute of Image Process and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0780305590

An FTTB (from top to bottom) design strategy for a neural network is introduced. From the scheme the authors present a design method and construct a generalized neural network which has some good qualitative behavior, e.g. any number of isolated prototypes can be set to asymptotically stable fixpoints, and any track converges to one of the equilibria. The time/space complexity of the model is O(mn), as opposed to O(nn) of Hopfield-like models. A simulation experiment shows its good recognition ability.< >

关键词： Network synthesis Neural networks Prototypes Brain modeling Nervous system Biological neural networks Neurons Circuits Power system modeling Costs

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MINIMUM ENTROPY DECONVOLUTION FOR RESTORATION OF BLURRED 2-TONE imageS

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ELECTRONICS LETTERS 1990年第15期26卷 1183-1184页

作者： WU, HS Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. China

A blind image restoration algorithm for noiseless blurred two-tone images based on the criterion of minimum entropy is presented. Performance of the algorithm is demonstrated by simulation.

关键词： blind image restoration algorithm computerised picture process.ng criterion of minimum entropy minimum entropy deconvolution restoration of blurred two-tone images simulation

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VELOCITY-FIELD COMPUTATION USING NEURAL NETWORKS

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ELECTRONICS LETTERS 1990年第21期26卷 1787-1790页

作者： HANBING, J Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. China

A new approach for optical flow (image velocity) fields computation is presented using computational neural networks. The computational procedure consists of three stages: estimation of the parameters of the neural network model, dynamic measurement of the perpendicular velocity components of the contours or region boundaries and computation of the image velocity fields. The parameters are estimated by comparing the energy function of the neural network with a constrained error function. The nonlinear velocity fields computation method is then carried out iteratively by using a dynamic algorithm to minimise the energy function simultaneously with the dynamic measurement of the perpendicular velocity components by a dynamic procedure. Experiments generate velocity fields that are meaningful and consistent with visual perception.

关键词： constrained error function dynamic algorithm dynamic measurement energy function image process.ng image velocity iterative method iterative methods neural nets neural network model nonlinear velocity fields computation method optical flow field computation parameters estimation perpendicular velocity components picture process.ng visual perception

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