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MINIMUM ENTROPY DECONVOLUTION FOR RESTORATION OF BLURRED 2-TONE imageS

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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Topology on image process.ng

Topology on image processing

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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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Car plate detection using cascaded tree-style learner based on hybrid object features

Car plate detection using cascaded tree-style learner based ...

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IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

作者： Wu, Qiang Zhang, Huaifeng Jia, Wenjing He, Xiangjian Yang, Jie Hintz, Tom Computer Vision Research Group University of Technology Sydney PO Box 123 Broadway NSW 2007 Australia Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. China

ISBN: (纸本)0769526888

Car plate detection is a key component in automatic license plate recognition system. This paper adopts an enhanced cascaded tree style learner framework for car plate detection using the hybrid object features including the simple statistical features and Harr-like features. The statistical features are useful for simplifying the process.on cascade classifier. The cascaded tree-style detector design will further reduce the false alarm and the false dismissal while retaining a high detection ratio. The experimental results obtained by the proposed algorithm exhibit the encouraging performance. © 2006 IEEE.

关键词： Object recognition

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Saliency Propagation from Simple to Difficult

Saliency Propagation from Simple to Difficult

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IEEE Conference on Computer Vision and pattern recognition

作者： Chen Gong Dacheng Tao Wei Liu S. J. Maybank Meng Fang Keren Fu Jie Yang Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781467369657

Saliency propagation has been widely adopted for identifying the most attractive object in an image. The propagation sequence generated by existing saliency detection methods is governed by the spatial relationships of image regions, i.e., the saliency value is transmitted between two adjacent regions. However, for the inhomogeneous difficult adjacent regions, such a sequence may incur wrong propagations. In this paper, we attempt to manipulate the propagation sequence for optimizing the propagation quality. Intuitively, we postpone the propagations to difficult regions and meanwhile advance the propagations to less ambiguous simple regions. Inspired by the theoretical results in educational psychology, a novel propagation algorithm employing the teaching-to-learn and learning-to-teach strategies is proposed to explicitly improve the propagation quality. In the teaching-to-learn step, a teacher is designed to arrange the regions from simple to difficult and then assign the simplest regions to the learner. In the learning-to-teach step, the learner delivers its learning confidence to the teacher to assist the teacher to choose the subsequent simple regions. Due to the interactions between the teacher and learner, the uncertainty of original difficult regions is gradually reduced, yielding manifest salient objects with optimized background suppression. Extensive experimental results on benchmark saliency datasets demonstrate the superiority of the proposed algorithm over twelve representative saliency detectors.

关键词： Teachers region of an image propagation Propagation image invariant image dilation

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Small target detection using an optimization-based filter

Small target detection using an optimization-based filter

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IEEE International Conference on Acoustics, Speech and Signal process.ng

作者： K. Xie K. Fu T. Zhou J. Yang Q. Wu X. He Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781467369985

Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely to cause false alarms. This paper proposes a novel method using an optimization-based filter to detect infrared small target in heavy clutter. First, we design a certain pixel area as active area. Second, a weighted quadratic cost function is performed in the active area. Finally, a filter based on statistics of active area is derived from the cost function. Our method could preserve heterogeneous area, meanwhile, remove target region. Experimental results show our method achieves satisfied performance in heavy clutter.

关键词： active area area statistics heavy clutter optimization-based filter small target detection Object detection useful area Filters Cost functions clutter

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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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