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An improved method of identification based on thermal palm vein image 1

19th International Conference on Neural information processing, ICONIP 2012

作者： Wang, Ran Wang, Guoyou Chen, Zhong Liu, Jianguo Shi, Yu 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 1037 Luoyu Road Hongshan District 430074 Wuhan Hubei Province China

ISBN: (数字)9783642344817

ISBN: (纸本)9783642344800

Biological characteristics based on face, fingerprint and iris images have been extensively studied and used for the identification in the past few decades. As a new-born method, thermal palm vein pattern is gathering more and more attention all over the world. An improved method of identification based on thermal palm vein image is presented in the paper. Five steps are needed to have a person verified: 1) acquisition of infrared palm vein image;2) detection of ROI (region of interest);3) enhancement of the palm vein image;4) features extraction of the palm vein patterns;5) matching the features between the real palm vein and sample data. Experiments have been carried out on 178 different images and 176 images of them are correctly recognized with two in failure. Experiments show the detection rate is satisfied. © 2012 Springer-Verlag.

关键词： Image enhancement

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Urban area detection using multiple Kernel Learning and graph cut

Urban area detection using multiple Kernel Learning and grap...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Chao Tao Yihua Tan Jin-gan Yu Jinwen Tian State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Patter Recognition and Artificial Intelligence Huazhong University of Science and Technology China

This paper presents a new method for urban detection from high-spatial-resolution satellite images. Unlike traditional approaches using only texture information for urban detection, we integrate several complementary image features through multiple Kernel Learning framework, and demonstrate that fusing multiple features can help improving urban detection accuracy rate. Furthermore, since that most of supervised urban classification approaches are mainly based on block-based image interpretation, the resulting urban boundary is very coarse. To handle this, we formulate the urban boundary refinement as a binary labeling problem, and propose a graph cut based approach to solve it. Experimental results show that the proposed approach outperforms the existing algorithm in terms of detection accuracy.

关键词： Feature extraction Training Urban areas Kernel Support vector machines Labeling Shape

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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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2012 3rd IEEE/IET International Conference on Audio, Language and Image processing, ICALIP 2012

作者： Zhu, Hu Deng, Lizhen Zhou, Gang Bai, Xiaodong Wang, Gaihua 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 1037 Luoyu Road Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

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. © 2012 IEEE.

关键词： Template matching

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Fast ground target detection method in infrared image sequences

Fast ground target detection method in infrared image sequen...

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2012 3rd IEEE/IET International Conference on Audio, Language and Image processing, ICALIP 2012

作者： Zhu, Hu Deng, Lizhen Wang, Gaihua Zhou, Gang Bai, Xiaodong 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 1037 Luoyu Road Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

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 multiframe 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. © 2012 IEEE.

关键词： Template matching

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Pneumoconiosis's Gross Tissue Imaging Classification based on Morphological Feature Description

Pneumoconiosis's Gross Tissue Imaging Classification based o...

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2012 Fifth International Symposium on Computational Intelligence and Design [第五届计算智能与设计国际会议 ISCID 2012]

作者： Delie Ming Linying Yu Liping Xiao State Key Laboratory for Multi-spectral Information Processing Technology Huazhong University of Sci Beijing Aerospace Automatic Control Institute Laboratory of Aerospace Intelligence Control Technolog

Referring to pneumoconiosis's gross tissue imaging classification, it is fatal to know the importance of distinguishing lung nodule from macule and how many nodules and macule the pneumoconiosis's gross tissue image really get. In achieving the distinguishing and counting results, the morphology processing method and some auxiliary digital image processing methods are adopted. After processing, the statistic work begins. The statistic results of abundant candidate parameters give us the chance to pick the parameter performing extremely well. In that way, the classification of pneumoconiosis's gross tissue images is quite feasible.

关键词： pneumoconiosis morphology Otsu segmentation lung nodule and macule sobel center extraction

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Fast template matching with partial skipping using sub-template

Fast template matching with partial skipping using sub-templ...

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2012 3rd IEEE/IET International Conference on Audio, Language and Image processing, ICALIP 2012

作者： Zhang, Qiao Gao, Huijie Kang, Zhen State Key Lab. of Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong Univ. of Sci. and Tech. Wuhan 430074 China School of Mathematic and Computer Science Wuhan Polytechnic University Wuhan 430023 China

ISBN: (纸本)9781467301718

This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the subtemplate size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method. © 2012 IEEE.

关键词： Global optimization

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Density compensation to reference map of gravity navigation

Density compensation to reference map of gravity navigation

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International Conference on Modelling, Identification and Control (ICMIC)

作者： Jie Ma Fan Yang Zu Yan Ling Xiong National Key Laboratory of Science and Technology on Multi-spectral Information Processing Huazhong University of Science and Technology Wuhan China College of information science and engineering Wuhan University of Science and Technology China

The current method of gravity gradient maps modeling is based on digital elevation model, the effects of isostasy in gravity gradient map modeling are researched and analyzed in this paper, and a novel method of modeling gravity gradient maps was presented. The current isostasy theory shows that the density of crust changes with elevation, so assigning a constant value to terrain's density is not accurate enough. At first, two kinds of isostasy model are analyzed, and on the basis of isostasy model, the gravity gradient map is modeled by using improved terrain density model. Then experimental results shows that Pratt model impose much more effects on gravity gradient map than Airy model. Consider the two models' effects in gravity gradient map modeling, Pratt Model has a great performance in the sea area, and Airy Model can be ignored the impact in the land area.

关键词： Atmospheric modeling Gravity Analytical models Geophysical measurements Digital elevation models Sea surface Navigation

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Ship detection in polarimetric SAR based on support vector machine

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Research Journal of Applied Sciences, Engineering and technology 2012年第16期4卷 2844-2850页

作者： Su, Xuwu Yang, Guangyou Sang, Hongshi State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China School of Mechanical Engineering Hubei University of Science and Technology Wuhan 430068 China

A Support Vector Machine (SVM) based method for ship detection in Polarimetric SAR (POLSAR) is proposed in this study. Because of similarities of ship and man-made structures on land in scattering mechanisms, land and sea are first segmented by SVM according to polarimetric features and texture features;The SVM-based Recursive Feature Elimination (RFE-SVM) approach is adopted to improve the performance of the segmentation algorithm. Then ship targets are extracted from sea by SVM classifier;Threshold-based rules and SVM-based rules are established for discriminating ship from non-ship target at last. The experiments are carried out on POLSAR data from Radarsat-2. For the available SAR images, the average accuracy of ship detection is over 95%. © Maxwell Scientific Organization, 2012.

关键词： Support vector machines

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Fast Template Matching with Partial Skipping Using Sub-template

Fast Template Matching with Partial Skipping Using Sub-templ...

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International Conference on Audio, Language and Image processing

作者： Qiao Zhang Huijie Gao Zhen Kang State Key Lab. of Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence School of Mathematic & Computer Science Wuhan Polytechnic University

ISBN: (纸本)9781467301732

This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the sub-template size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method.

关键词： Computational efficiency Prediction algorithms Search problems Accuracy Correlation Signal processing algorithms Pattern recognition

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Fast Ground Target Detection Method in Infrared Image Sequences

Fast Ground Target Detection Method in Infrared Image Sequen...

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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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