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International Conference on Audio, Language and image processing

作者： Hu Zhu Lizhen Deng Gaihua Wang Gang Zhou Xiaodong Bai National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology College of Electrical & Electronic Engineering Huazhong University of Science and Technology

ISBN: (纸本)9781467301732

Automatic target detection (ATD) in infrared (IR) imagery is a fundamental and challenging task in computer vision. A fast automatic target detection method in IR image sequence is proposed in this paper. Since the position and scale of target change real-timely, we can predict the target position in real-time image by using the history position of target and flight parameters information of previous and current frames, and then estimate the scale of target depending on flight parameters and imaging parameters for getting the model with the appropriate scale. In order to make the template matching more robust for target rotation, the template matching method based on parametric template vector is used to recognize the position of target. The detection result is identified by using multi-frame integration based on recognition information of history and currant frames. Some experimental results using real-world images with complicated background validate the effectiveness and robustness of the proposed method under rotation and scale variance condition.

关键词： Infrared imaging images Targets flight parameter computer vision real image fast ground infrared imagery automatic target currant Object detection TEMPLATE MATCHING Scale formation

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Alignment, segmentation and 3-D reconstruction of serial sections based on automated algorithm

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AIP Conference Proceedings 2012年第1期1504卷 1287-1292页

作者： Weiguo Bian Shaojie Tang Qiong Xu Qin Lian Jin Wang Dichen Li State Key Lab for Manufacturing System Engineering Xi 'an Jiaotong University Xi 'an 710049 P.R.China and The First Affiliated Hospital Medical College Xi 'an Jiaotong University Xi 'an 710049 China School of Automation Xi'an University of Posts and Telecommunications Xi'an 710121 P.R.China and Institute of Image Processing & Pattern Recognition Xi'an Jiaotong University Xi'an 710049 China Institute of Image Processing & Pattern Recognition Xi'an Jiaotong University Xi'an 710049 China State Key Lab for Manufacturing System Engineering Xi 'an Jiaotong University Xi 'an 710049 China The Second Affiliated Hospital Medical College Xi'an Jiaotong University Xi'an Shaanxi 710121 China

A well-defined three-dimensional (3-D) reconstruction of bone-cartilage transitional structures is crucial for the osteochondral restoration. This paper presents an accurate, computationally efficient and fully-automated algorithm for the alignment and segmentation of two-dimensional (2-D) serial to construct the 3-D model of bone-cartilage transitional structures. Entire system includes the following five components: (1) image harvest, (2) image registration, (3) image segmentation, (4) 3-D reconstruction and visualization, and (5) evaluation. A computer program was developed in the environment of Matlab for the automatic alignment and segmentation of serial sections. Automatic alignment algorithm based on the position's cross-correlation of the anatomical characteristic feature points of two sequential sections. A method combining an automatic segmentation and an image threshold processing was applied to capture the regions and structures of interest. SEM micrograph and 3-D model reconstructed directly in digital microscope were used to evaluate the reliability and accuracy of this strategy. The morphology of 3-D model constructed by serial sections is consistent with the results of SEM micrograph and 3-D model of digital microscope.

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Target recognition method based on template matching in downward-looking infrared image

Target recognition method based on template matching in down...

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International Conference on Audio, Language and image processing, ICALIP

作者： Hu Zhu Lizhen Deng Gang Zhou Xiaodong Bai Gaihua Wang National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China College of Electrical & Electronic Engineering Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781467301732

Automatic ground target recognition technology in downward-looking infrared imagery is challenging problems due to the complexity of real-world. A robust ground target recognition method is proposed for downward-looking infrared (DLIR) image sequences in this paper. A complete model of the proposed method is designed firstly and the principles of some key technologies are introduced as following. Perspective transformation is used to solve the projective problems of landmark translation, rotation and scale variance in real-time image sequence. The size of landmark is estimated real-timely by using flight parameters and imaging parameters for getting the model with an appropriate scale. Based on the matching results of landmark and flight parameters, target position technology is proposed to identify the position of target by using the position relation between landmark and target. Experimental results using real-world image data with complicated background showed that the proposed method not only causes high precisely locating results, but also has good robustness for target occlusion.

关键词： Target recognition Satellites image sequences Real-time systems Robustness Imaging Aircraft

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Numerical simulation on magnetic flux leakage testing of the steel cable at different speed title

Numerical simulation on magnetic flux leakage testing of the...

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International Conference on Electronics and Optoelectronics

作者： Gan, Zhihua Chai, Xiuli Computer Center Henan Universitye Kaifeng 475001 China Institute of Image Processing and Pattern Recognition College of Computer and Information Engineering Henan University Kaifeng 475001 China

ISBN: (纸本)9781612842738

The safety operation of steel cable is vital and the cable should be maintained through regular inspection. Magnetic flux leakage (MFL) method is a popular inspection technique. For the online nondestructive testing (NDT), the eddy current arises in the steel cable due to the relative movement of the cable and the MFL system, which affects the defect field and causes the difficulty in the defect inspection. In this paper, for axial MFL system with permanent magnet excitation at different speeds, the distribution of eddy currents, magnetic flux lines and magnetic leakage field are investigated by numerical simulation. The results provide a deep insight into the design of the MFL system. © 2011 IEEE.

关键词： Cables

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Design and characteristic analysis of giant magnetoimpedance sensor in Fe-based nanocrystalline ribbons

Design and characteristic analysis of giant magnetoimpedance...

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International Conference on Electronics and Optoelectronics

作者： Chai, Xiuli Gan, Zhihua Institute of Image Processing and Pattern Recognition College of Computer and Information Engineering Henan University Kaifeng 475001 China Computer Center Henan University Kaifeng 475001 China

ISBN: (纸本)9781612842738

A magnetic sensor based on giant magnetoimpedance effect (GMI) was developed. The basic element of the sensor is a Fe-based nanocrystalline ribbon of composition Fe73.5Cu1Nb3Si13.5B9. A sensitivity of 0.6691 V/Oe for the linear sensor was obtained, and the linear correlation coefficient reaches 0.9657 in the range of ±4.5 Oe. © 2011 IEEE.

关键词： Magnetic sensors

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An adaptive mean shift algorithm based on LSH

An adaptive mean shift algorithm based on LSH

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2011 International Conference on Power Electronics and engineering Application

作者： Yanbin Cui Kui Cao Gang Zheng Fan Zhang College of Computer and Information Engineering Henan University Institute of Image Processing and Pattern Recognition Henan University

The time complexity of the adaptive mean shift is related to the dimension of data and the number of iterations. The computational complexity will increase proportionally with the increase of the data dimension. An approximate neighborhood queries method is presented for the computation of high dimensional data, in which, the localitysensitive hashing(LSH) is used to reduce the computational complexity of the adaptive mean shift algorithm. Experimental results show that the proposed algorithm can reduce the complexity of the adaptive mean shift algorithm and can produce a more accurate classification than the fixed bandwidth mean shift algorithm.

关键词： pattern Classification Adaptive bandwidth Adaptive mean-shift Locality-sensitive hashing

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Position identification by actively localizing spacial sound beacons

Position identification by actively localizing spacial sound...

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作者： Li, Huakang Huang, Jie Zhao, Qunfei School of Computer Science Engineering University of Aizu Aizuwakamatsu-shi 965-8580 Japan Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

In this paper, we propose a method for robot self-position identification by active sound localization. This method can be used for autonomous security robots working in room environments. A system using an AIBO robot equipped with two microphones and a wireless network is constructed and used for position identification experiments. Differences in arrival time to the robot's microphones are used as localization cues. To overcome the ambiguity of front-back confusion, a three-head-position measurement method is proposed. The position of robot can be identified by the intersection of circles restricted using the azimuth differences among different sound beacon pairs. By localizing three or four loudspeakers as sound beacons positioned at known locations, the robot can identify its position with an average error of 7 cm in a 2.5 × 3.0m2 working space in the horizontal plane. We propose adjusting the arrival time differences (ATDs) to reduce the errors caused when the sound beacons are high mounted. A robot navigation experiment was conducted to demonstrate the effectiveness of the proposed position-identification system. © 2011 The institute of Electronics, information and Communication Engineers.

关键词： Robots

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Accurate moving object detection in thermal imagery

Accurate moving object detection in thermal imagery

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IEEE International Conference on computer Science and Automation engineering (CSAE)

作者： Zhang, Yan Zhao, Ting Gu, Jian Yu, Shengyang Testing Center of Security Products for Computer Information System Ministry of Public Security Quality Supervision Ministry of Public Security Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424487257

Accurate detection of moving object provides a fundamental capability that drives numerous high-level computer vision applications. In this paper, a novel algorithm is proposed to detect objects in widely varying thermal imagery. On the basis of properties of thermal imagery, effective foreground and background model are first presented, and then these models are competitively used in an unified MAP-MRF framework to detect objects. Experimental results on challenging dataset show the robustness and effectivity of the proposed algorithm. © 2011 IEEE.

关键词： Object detection

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An Adaptive Mean Shift Algorithm Based on LSH

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Procedia engineering 2011年 23卷 265-269页

作者： Yanbin Cui Kui Cao Gang Zheng Fan Zhang College of Computer and Information Engineering Henan University Kaifeng Henan 475001 PR China Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan 475001 PR China Kaifeng Electric Power Company Kaifeng 475001 PR China

The time complexity of the adaptive mean shift is related to the dimension of data and the number of iterations. The computational complexity will increase proportionally with the increase of the data dimension. An approximate neighborhood queries method is presented for the computation of high dimensional data, in which, the locality-sensitive hashing (LSH) is used to reduce the computational complexity of the adaptive mean shift algorithm. Experimental results show that the proposed algorithm can reduce the complexity of the adaptive mean shift algorithm and can produce a more accurate classification than the fixed bandwidth mean shift algorithm.

关键词： pattern Classification Adaptive bandwidth Adaptive mean-shift Locality-sensitive hashing

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Multi-temporal Satellite images Change Detection Algorithm Based on NSCT

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Procedia engineering 2011年 24卷 252-256页

作者： Wei Cui Zhenhong Jia Xizhong Qin Jie Yang Yingjie Hu College of Information Science and Engineering Xinjiang University Urumqi 830046 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland 1020 New Zealand

In order to get the change detection *** unsupervised change detection algorithm for multi-temporal satellite image based on NSCT (non-subsampling contourlet transform) and k-means clustering is proposed in this paper. For each pixel in the log-ratio image, multi-scale and multi-direction feature vector is extracted by NSCT and the reconstruction of the log-ratio image is obtained. The threshold is produced by using the k-means clustering algorithm and can distinguish between the unchanged and the change region. Finally, the change detection map is achieved. Some satellite images are used to verify the proposed method and the results shows that it has a higher stability and accuracy against Gaussian and speckle noise than traditional algorithms.

关键词： NSCT k-means clustering multi-temporal satellite images change detection

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