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Multi-feature bio-inspired model for scene classification

Applied Mechanics and Materials 2013年 303-306卷 1569-1572页

作者： Hu, De-Kun Lin, Jie College of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province 610106 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9783037856529

A multi-feature bio-inspired model for scene image classification (MFBIM) is presented in this work;it extends the hierarchical feedforward model of the visual cortex. Firstly, each of three paths of classification uses each image property (i.e. shape, edge or color based features) independently. Then, BPNN assigns the category of an image based on the previous outputs. Experiments show that the model boosts the classification accuracy over the shape based model. Meanwhile, the proposed approach achieves a high accuracy comparable to other reported methods on publicly available color image dataset. © (2013) Trans Tech Publications, Switzerland.

关键词： Computer vision

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LPQ based static and dynamic modeling of facial expressions in 3D videos

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2012 International Conference on Service-Oriented Computing, ICSOC 2012

作者： Zhen, Qingkai Huang, Di Wang, Yunhong Chen, Liming Laboratory of Intelligent Recognition and Image Processing School of Computer Science and Engineering Beihang University Beijing China Ecole Centrale de Lyon LIRIS UMR5205 F-69134 Lyon France

ISBN: (纸本)9783319029603

Automatic Facial Expression recognition (FER) is one of the most active topics in the domain of computer vision and pattern recognition. In this paper, we focus on discrete facial expression recognition by using 4D data (i.e. 3D range image sequences), and present a novel method to address such an issue. The Local Phase Quantisation from Three Orthogonal Planes (LPQ-TOP) descriptor is applied to extract both the static and dynamic clues conveyed in facial expressions. On the one hand, it locally captures the shape attributes in each 3D face model (facial range image). On the other hand, it detects the latent temporal information and represents dynamic changes occurred in facial muscle actions. The SVM classifier is finally used to predict the expression type. The experiments are carried out on the BU-4DFE database, and the achieved results demonstrate the effectiveness of the proposed method. © Springer International Publishing 2013.

关键词： Face recognition

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Fuzzy headlight intensity controller using wireless sensor network

Fuzzy headlight intensity controller using wireless sensor n...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Victor Nutt Shubhalaxmi Kher Mehul Raval Electrical Engineering Arkansas State University Jonesboro USA Pattern Recognition and Image Processing Group DAIICT Gandhinagar India

ISBN: (纸本)9781479900213

This paper addresses the issue of headlight intensity to alleviate glare and blinding during night for drivers. Many factors are considered when analyzing automobile transportation in order to increase safety. One of the most prominent factors for night-time travel is temporary blindness due to elevated headlight intensity. This is particularly prominent on single lane roads. While headlight intensity provides better visual acuity, it inversely affects oncoming traffic. This problem is compounded when both drivers are using a higher headlight intensity setting. Also, higher speed due to decreased traffic levels at night increases the severity of accidents. In order to eliminate accidents due to temporary driver blindness, a fuzzy controller is designed based on the data captured using a wireless sensor network (WSN). Low latency allows quicker headlight intensity adjustment to minimize temporary blindness. Multiple attributes are taken into consideration for controller design. The results show that controller output is nearly instantaneous and generates control signal continuously.

关键词： Vehicles Roads Meteorology Wireless sensor networks Fuzzy logic Sensors

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Placement and selection algorithm of reference nodes in WSN localization

Placement and selection algorithm of reference nodes in WSN ...

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6th China Conference of Wireless Sensor Networks, CWSN 2012

作者： Min, Lin Li, Hui Guo, Zhengwei Network Information Center Office Henan University Kaifeng Henan 475001 China Henan University Minsheng College Kaifeng Henan 475004 China School of Computer and Information Engineering Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan 475001 China

ISBN: (纸本)9783642362514

Currently, few studies of wireless sensor network node localization algorithm were focused on the reference nodes, but how to choose and place reference nodes has a great influence on the positioning accuracy. In order to quantitatively study this issue, we proved a theorem, which describes the relationship between the placement of reference nodes and whether the node can be located, then the reference nodes placement method was designed. Finally, a reference nodes selection algorithm was proposed based on the condition number of linear equations, so as to improve the accuracy of range-based localization algorithm. © 2013 Springer-Verlag.

关键词： Number theory

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Improved DV-hop localization algorithm based on RSSI value and hop correction

Improved DV-hop localization algorithm based on RSSI value a...

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6th China Conference of Wireless Sensor Networks, CWSN 2012

作者： Guo, Zhengwei Min, Lin Li, Hui Wu, Wenjian School of Computer and Information Engineering Institute of Image Processing and Pattern Recognition Henan University Kaifeng Henan 475001 China Network Information Center Office Henan University Kaifeng Henan 475001 China Henan University Minsheng College Kaifeng Henan 475004 China

ISBN: (纸本)9783642362514

On the basis of the analysis of the relation between network's topologyand localization precisionan improved DV-Hop algorithm based on hop correction is put forward. Firstly, RSSI value is used to correct the distance between unknown node and reference nodes in the range of single hop;secondly, a certain amount of correction value is added to the original hop between unknown node and reference nodes to further reduce the distance error between them. Simulation result shows that improved algorithm improves the localization precision. © 2013 Springer-Verlag.

关键词： correction DV-Hop WSN

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Dynamic monitoring technique for remote-sensing image of invasive alien plant species

Dynamic monitoring technique for remote-sensing image of inv...

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2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013

作者： Hesen, Rabigul Jia, Zhenhong Yang, Jie Hu, Raphael 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

ISBN: (纸本)9783642419072

Invasive Alien Plant Species (IAPS) could seriously affect the local ecosystem balance, and pose a threat to the ecological security. In order to effectively monitor and control invasive alien plants, it needs to monitor the spatial distribution and dynamic changes of IAPS. It will cite the method of nonsubsampled contourlet transform (NSCT) combination with fuzzy C-means clustering algorithm in this paper, which is used in remote sensing image change detection, for monitoring the dynamic changes of biological invasive species in this paper, to get a better detection result. © Springer-Verlag Berlin Heidelberg 2013.

关键词： image enhancement

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Detection of aflatoxin contaminated figs using Near-Infrared (NIR) reflectance spectroscopy

Detection of aflatoxin contaminated figs using Near-Infrared...

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International Conference on Electronics, Computer and Computation (ICECCO)

作者： Ali Güneş Habil Kalkan Efkan Durmuş Mehmet Burak Bütükcan Vision Image Processing and Pattern Recognition Laboratory (VIPLAB) S üleyman Demirel University Isparta Turkey Canakkale Onsekiz Mart Universitesi Canakkale Canakkale TR

Figs like other agricultural products may include cancerogenic aflatoxin which is caused by Aspergillus type molds. Under the UV illumination, a large portion of the aflatoxin contaminated figs expose Bright Greenish Yellow Fluorescence (BGYF) in visible light spectrum. Using the fluorescence properties, the contaminated figs are visually detected and manually removed by workers. However, this procedure could not eliminate all the aflatoxin contaminated figs and the UV exposure may cause skin cancer on workers under UV illumination. Besides, the reflectance outside the visible spectrum may include significant information for aflatoxin contamination. In this study, we investigate the NIR reflectance spectroscopy for the detection of aflatoxin contaminated figs and correctly classified the figs with 90% mean accuracy.

关键词： Spectroscopy Reflectivity Fluorescence Lighting Inspection Sugar Contamination

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Novel change detection method based on direction feature and fuzzy clustering for remote sensing images and its application in biological invasions

Novel change detection method based on direction feature and...

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2013 International Conference on Geo-Informatics in Resource Management and Sustainable Ecosystem, GRMSE 2013

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

ISBN: (纸本)9783642419072

Change detection techniques attempt to be used for remote sensing monitoring of invasive plants. A novel change detection method based on direction feature and RFLICM (an improved fuzzy C-means clustering) is proposed. Firstly, the difference image is acquired from multitemporal images. The pixel values of the difference image are updated using the template of directional neighborhood based on direction feature. The final change detection map is achieved by clustering the pixel values of the difference image using RFLICM algorithm into two disjoint classes: changed and unchanged. The results obtained by experiment are compared with some other existing state of the art methods. It is observed that the proposed method outperforms the other methods. Finally, the proposed change detection technique is applied to remote sensing monitoring of invasive plants. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Change detection

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Parallel implementation of segmentation algorithms on graphics processing unit

Parallel implementation of segmentation algorithms on graphi...

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IEEE Signal processing and Communications Applications (SIU)

作者： Erdal Yenialp Habil Kalkan Vision Image Processing and Pattern Recognition Laboratory (VIPLAB) Bilgisayar Mühendisliği Bölümü Süleyman Demirel Üniversitesi Isparta Turkey

Segmentation algorithms are widely used in image processing. These methods have different complexity values and the choice of reasonable methods decreases on large images. Especially on the medical images with large size, it may take days to perform segmentation in some methods. However, parallel implementation may eliminate the drawback of these algorithms to some extent. In this study, we propose to implement segmentation algorithms in parallel using Graphical processing Unit. Using the proposed implementation, the computation time of the K-centers, K-means and DBSCAN algorithms were decreases 87, 642 and 2 times, respectively.

关键词： Graphics processing units Clustering algorithms image segmentation Art Software algorithms Computer science

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AFFINE SOFTASSIGN WITH BIDIRECTIONAL DISTANCE FOR POINT MATCHING

AFFINE SOFTASSIGN WITH BIDIRECTIONAL DISTANCE FOR POINT MATC...

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IEEE International Conference on image processing

作者： Peng-peng Zhang Sheng-zheng Wang Yu Qiao Jie Yang Yong-hui Gao The Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China 200240 Merchant Marine College Shanghai Maritime University China 200235

ISBN: (纸本)9781479923427

This paper proposes a new affine registration algorithm for 2D point matching. It is a two-step iterative registration algorithm by soft weight assignment based on bidirectional distance. At each iteration, the affine transformation is updated by two optimization steps, in which the model data and the test data are matched from each other respectively. By the optimization of registration at separate steps during each iteration, the proposed algorithm can provide a good estimate of the accurate affine transformation in condition of poor initialization and lack of geometric assumptions on point sets. Some experiments about comparison with the current state-of-the art approaches, demonstrate the robustness and accuracy of our method.

关键词： affine soft assignment bidirectional distance point matching In-law Affine transformation Bidirectional Affine Registration observational data iterative methods

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