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International Conference on Natural Computation (ICNC)

作者： Hua Zhou Chao Cai Mingyue Ding Institute of Pattern Recognition and Artificial Intelligence National Laboratory of Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan China School of Life Science and Technology Imaging Processing and Intelligence Control Key Laboratory of Education Ministry Huazhong University of Science and Technology Wuhan China

Object recognition is challenging problem in computer vision due to appearance variation and presence of visual clutter and occlusions. Recently manifolds are thought to be fundamental for visual perception, and manifold learning algorithms are developed for discovering intrinsical features. Selective visual attention mechanism provides tools to reduce computation cost and avoid the influence of clutter background. In this paper, we described a new object recognition method, the submanifold distance (SMD) algorithm, which is induced by the visual attention mechanism to provide complex object recognition. Experiments with airport remote sensing images illustrated that our proposed algorithm can recognize complex objects accurately, robustly and quickly.

关键词： Manifolds Visualization Airports Clutter Target recognition image recognition

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Age Classification Base on Gait Using HMM

Age Classification Base on Gait Using HMM

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International Conference on pattern recognition

作者： De Zhang Yunhong Wang Bir Bhanu Intelligent Recognition and Image Processing Laboratory School of Computer Science and Engineering Beihang University Beijing China Center of Research in Intelligent Systems University of California Riverside CA USA

In this paper we propose a new framework for age classification based on human gait using Hidden Markov Model (HMM). A gait database including young people and elderly people is built. To extract appropriate gait features, we consider a contour related method in terms of shape variations during human walking. Then the image feature is transformed to a lower-dimensional space by using the Frame to Exemplar (FED) distance. A HMM is trained on the FED vector sequences. Thus, the framework provides flexibility in the selection of gait feature representation. In addition, the framework is robust for classification due to the statistical nature of HMM. The experimental results show that video-based automatic age classification from human gait is feasible and reliable.

关键词： Hidden Markov models Senior citizens Databases Legged locomotion Feature extraction Humans Pixel

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Registration-based auto-detection of the optimal cross sections in 3D echocardiographic images

Registration-based auto-detection of the optimal cross secti...

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International Conference on Bioinformatics and Biomedical Technology (ICBBT)

作者： Xiaoping Liu Xin Yang Lanping Wu Xiao Tan Computer Center East China Jiao Tong University Shanghai China Institute of Pattern recognition and Image Processing Shanghai Jiaotong University Shanghai China Children's Medical Center Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424467754;9781424467761

In most cases, echocardiographers examine three-dimensional (3D) or four-dimensional (4D) echocardiographic images by studying several important cross sections which are defined as the optimal cross sections. It is a time-consuming and tedious task for echocardiographers to manually search the optimal cross sections by existing real-time 3D echocardiography (RT3DE) systems or off-line 3D softwares. To assist doctors' diagnosis, we design a registration-based method to automatically detect the optimal cross sections in three-dimensional echocardiographic (3DE) images. Firstly, a normal end-diastolic (ED) volumetric data is chosen, in which its optimal cross section is predetermined. Secondly, instead of the whole ED volume, only part of it is selected as the template. Finally, all the optimal cross sections of a 3DE image are detected by aligning the 3DE image with the template image. As a preliminary study, we performed this method on 28 normal apical datasets and the error rate is 15%. The results show good prospects for implementing automatic detection, which might offer better repeatability and save time. Furthermore, it can be a prior procedure for measurement and the computer-aided diagnosis.

关键词： Ultrasonic imaging image registration Heart Biomedical imaging Echocardiography Medical diagnostic imaging image reconstruction Shape pattern recognition image processing

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Efficient Joint 2D and 3D Palmprint Matching with Alignment Refinement

Efficient Joint 2D and 3D Palmprint Matching with Alignment ...

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IEEE Conference on Computer Vision and pattern recognition

作者： Wei Li Lei Zhang David Zhang Guangming Lu Jingqi Yan Biometrics Research Center Dept. of Computing The Hong Kong Polytechnic University Biocomputing Research Center Shenzhen Graduate School Harbin Institute of Technology Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University

ISBN: (纸本)9781424469840;9781424469857

Palmprint verification is a relatively new but promising personal authentication technique for its high accuracy and fast matching speed. Two dimensional (2D) palmprint recognition has been well studied in the past decade, and recently three dimensional (3D) palmprint recognition techniques were also proposed. The 2D and 3D palmprint data can be captured simultaneously and they provide different and complementary information. 3D palmprint contains the depth information of the palm surface, while 2D palmprint contains plenty of textures. How to efficiently extract and fuse the 2D and 3D palmprint features to improve the recognition performance is a critical issue for practical palmprint systems. In this paper, an efficient joint 2D and 3D palmprint matching scheme is proposed. The principal line features and palm shape features are extracted and used to accurately align the palmprint, and a couple of matching rules are defined to efficiently use the 2D and 3D features for recognition. The experiments on a 2D+3D palmprint database which contains 8000 samples show that the proposed scheme can greatly improve the performance of palmprint verification.

关键词： Dermatoglyphics Three Dimensions

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A method for improving the accuracy of predicting protein localization

A method for improving the accuracy of predicting protein lo...

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The 5th International Conference on Computer Science & Education(第五届国际计算机新技术与教育学术研讨会 ICCSE'10)

作者： Tong Wang Qinghua Huang Lixiu Yao Institute of Computer and Information Shanghai Second Polytechnic UniversityShanghai201209China School of Communication and Information Engineering Shanghai University Shanghai200444China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong UniversityShanghai200240C

In this paper, a system based on the novel Maximum Variance Projection (MVP) is proposed to improve the performance of protein subcellular localization prediction. Firstly, the protein sequences are quantized into a high dimension space using a new representation approach Position-Specific Score Matrix (PSSM). However, the problems caused by such representation are computation complexity and complicated classifier design. To sort out this problem, a new dimension reduction algorithm, MVP, is introduced. It extracts the essential features from the high dimension feature space. Then, K-Nearest Neighbor (K-NN) classifier is employed to recognize the subcellular localization of proteins according to the new features after dimension reduction. A good experimental result is obtained based on the jackknife dataset.

关键词： Subcellular localization:Dimensionality reduction:PSSM

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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IEEE International Conference on Mechatronics and Automation

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan China College of Mechanical Engineering TaiYuan University of Technology TaiYuan China Institute for Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology WuHan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Degradation Atmospheric modeling Optical scattering Optical imaging

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Study on the Method of image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： image edge detection image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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Pose estimation based on human detection and segmentation

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Science in China(Series F) 2009年第2期52卷 244-251页

作者： CHEN Qiang ZHENG EnLiang LIU YunCai Institute of image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

We address the problem of 3D human pose estimation in a single real scene image. Normally, 3D pose estimation from real image needs background subtraction to extract the appropriate features. We do not make such assumption, In this paper, a two-step approach is proposed, first, instead of applying background subtraction to get the segmentation of human, we combine the segmentation with human detection using an ISM-based detector. Then, silhouette feature can be extracted and 3D pose estimation is solved as a regression problem. RVMs and ridge regression method are applied to solve this problem. The results show the robustness and accuracy of our method.

关键词： human detection and segmentation 3D pose estimation regression machine learning

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Evaluating deformation patterns of the thoracic aorta in gated CTA sequences

Evaluating deformation patterns of the thoracic aorta in gat...

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IEEE International Symposium on Biomedical Imaging

作者： Ernst Schwartz Roman Gottardi Johannes Holfeld Christian Loewe Martin Czerny Georg Langs Computational Image Analysis and Radiology Lab (CIR) Medical University of Vienna Austria Pattern Recognition and Image Processing Group University of Technology Vienna Austria Division of Cardiothoracic Surgery Department of Surgery Medical University of Vienna Austria Division of Interventional Radiology Department of Radiology Medical University of Vienna Austria Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology USA

ISBN: (纸本)9781424441259;9781424441266

Cardiovascular interventions in the region of the aortic isthmus such as stent-grafting and vessel transposition introduce substantial changes in the deformation properties of the affected vessels. The changes play a fundamental role in the long-term prognosis for any such treatment, but are only poorly understood to date. We explore a fully automated method to quantify the deformation patterns of the thoracic aorta in gated computed tomography sequences. The aorta is segmented by a level set approach that accurately identifies the vessel lumen in each frame of the sequence. Consequently, landmarks on the vessel wall in each frame are registered using a probabilistic method. This allows for the measurement of global and local deformation properties. We evaluate our method on synthetic datasets and report first results of its application on real world data.

关键词： Biomedical imaging image segmentation Radiology Cardiology Surgery Computed tomography Level set Electrocardiography Pathology Deformable models

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An image-Sequence Compressing Algorithm Based on Homography Transformation for Unmanned Aerial Vehicle

An Image-Sequence Compressing Algorithm Based on Homography ...

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International Symposium on Intelligence Information processing and Trusted Computing (IPTC)

作者： Junbin Gong Chenlin Zheng Jinwen Tian Dingxue Wu Institute for Pattern Recognition and Artificial Intelligence National key laboratory of science and technology on multi-spectral information processing Huazhong University of Science and Technology Wuhan China College of Computer Science and Technology Huanggang Normal University Huangang China

Focus on the image compressing problem of unmanned aerial vehicle with high compression ratio, fixed compressing ratio and low computational complexity requirement, a low-complexity image-sequence compressing algorithm based on homography transformation was proposed. The image sequences were dynamically divided into frame-groups according the data from airborne inertial navigation systems, and the intermediate frames in the same frame-group was b i-directionally predicted by the first-frame and the end-frame with homography transformation. The homography matrix was got approximately by the airborne inertial navigation systems firstly and then was accurately computed by fast multiple sub-areas template matching. At the end the first frame and the residual images of the intermediate frames of the same frame-group was merged into a big image and coded by JPEG2000 to generate fixed-size code streams. The experiment results show that the proposed algorithm was with high compression performance, low computational complexity and excellent capacity for code-size control and will has good prospect in engineer.

关键词： image coding Unmanned aerial vehicles Cameras Transform coding image restoration image sequences Heuristic algorithms

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