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MULTIPLE FEATURES-BASED IMAGE RETRIEVAL

2011 4th IEEE International Conference on Broadband Network & Multimedia Technology(第四届IEEE宽带网络与多媒体国际会议 4th IEEE IC-BNMT2011)

作者： Yanyan Gao Honggang Zhang Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China

Color and texture information are two important visual features of an image. In this paper, an efficient content-based image retrieval system is proposed based on color and texture feature. The color feature is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by color histogram. Texture feature is obtained by local binary pattern (LBP). When computing the similarity between query image and target images in the database, Gaussian normalization is exploited on the feature space and distant space. And then the linear combination of normalized distances for color and texture is performed to obtain the similarity as the index of image. The exhaustive search scheme is used for retrieval, and the evaluation criterion is precision and recall about the number of returned images. The results of experiments demonstrate the efficiency of the proposed system.

关键词： content-based image retrieval color feature texture feature multi-feature

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A DSP/FPGA -based parallel architecture for real-time image processing

A DSP/FPGA -based parallel architecture for real-time image ...

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6th World Congress on intelligent Control and Automation, WCICA 2006

作者： Luxin, Yan Tianxu, Zhang Sheng, Zhong Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)1424403324

DSP/FPGA-based parallel architecture oriented to real-time Image processing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnection network and the specific data communication protocol are implemented, which interconnect 3 DSPs (TMS320C6414) effectively. The measured performances in the prototype with the proposed parallel architecture, including inter-DSP data communication performance and system computing capacity, show high data transfer bandwidth (up to 400 Mbytes/s) with low latency as well as high image processing performance, which achieve a good balance for parallel Image processing. © 2006 IEEE.

关键词： Digital signal processing

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Smoke Image Segmentation Based on Color Model

Smoke Image Segmentation Based on Color Model

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第11届创新与管理国际学术会议（ICIM2014）

作者： Deng Xing Yu Zhongming Wang Lin Li Jinlan School of Science Guizhou Minzu University Guizhou provincial key laboratory of pattern recognition and intelligent system Liupanshui Normal University

Smoke is the most significant feature in the process of fire,so it's possible to rely on smoke detection to detect *** the smoke image segmentation is the most difficult and also indispensable step in the analysis of smoke image *** order to improve its accuracy and effectively exclude the disturbances of non-smoke image,and lower the false alarm rate,it puts forward a kind of smoke image segmentation based on color *** uses K-means clustering in Lab color space and threshold segmentation in HSV color space,then merges the two ***,it uses the method of shen filter and regional mark to denoise,Experimental results on segmentation of smoke image show that the proposed method is able to segment smoke from the background.

关键词： Image segmentation K-means algorithm Color space LAB HSV

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Autonomous Obstacle Avoidance Scheme Using Monocular Vision Applied to Mobile Robots

Autonomous Obstacle Avoidance Scheme Using Monocular Vision ...

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2020 International Conference on intelligent Control, Measurement and Signal Processing and intelligent Oil Field, ICMSP 2020

作者： Song, Yun Yun Yang, Sheng Yi Liu, Chao Wu, Qing Gui School of Data Science and Information Engineering Key Laboratory of Pattern Recognition and Intelligent Systems of Guizhou Province Guizhou Minzu University Guiyang China School of Mechatronics Engineering Guizhou Minzu University Guiyang China

Mobile robots cannot move in an unknown environment with static or slow-moving obstacles effectively. We present an enhanced obstacle avoidance strategy using monocular vision to solve this problem. First, we combine Canny and Otsu to extract the barrier feature and find the critical pixel position of obstacles by the monocular vision. Then the image depth estimation algorithm is used to estimate the gaps. With these parameters of barriers, an improved bug algorithm is proposed to avoid the obstacles autonomously. The experiments show that the proposed obstacles avoidance strategy can effectively make a small mobile robot avoid different kinds of obstacles. © Published under licence by IOP Publishing Ltd.

关键词： Mobile robots

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An Image Matching Evolutionary Algorithm Based on Hu Invariant Moments

An Image Matching Evolutionary Algorithm Based on Hu Invaria...

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2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

作者： Ruliang Zhang Lin Wang Key Laboratory of Pattern Recognition and Intelligent Control Guizhou University for NationalitiesGuiyang China

ISBN: (纸本)9781612848792

This paper presents an image matching evolutionary algorithm (called IMEA algorithm) based on Hu invariant moments. First, the population is initialized. A group of searched subgraphs is constructed. Second, the fitness function based on Hu invariant moments is designed. The seven Hu invariant moments of the template image and the searched subgraph are calculated. The Euclidean distance of Hu invariant moments is used to measure similarity between the template image and the searched subgraph. The template image and the searched subgraph are matched if these Euclidean distances are less than the set threshold. Finally, a new searched subgraph is constructed by means of a new evolutionary strategy. The new searched subgraph replaces the searched subgraph whose value of the fitness function is maximum. Experimental results demonstrate the great robustness and efficiency of the IMEA algorithm.

关键词： Hu invariant moments evolutionary algorithm euclidean distance image matching

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Feature Selection Based on Adaptive Fuzzy Membership Functions

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自动化学报 2006年第4期32卷 496-503页

作者： XIE Yan-Tao SANG Nong ZHANG Tian-Xu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074

Neuro-fuzzy(NF)networks are adaptive fuzzy inference systems(FIS)and have been applied to feature selection by some ***,their rule number will grow exponentially as the data dimension *** the other hand,feature selection algorithms with artificial neural networks(ANN)usually require normalization of input data,which will probably change some characteristics of original data that are important for *** overcome the problems mentioned above,this paper combines the fuzzification layer of the neuro-fuzzy system with the multi-layer perceptron(MLP)to form a new artificial neural ***,fuzzification strategy and feature measurement based on membership space are proposed for feature selection. Finally,experiments with both natural and artificial data are carried out to compare with other methods,and the results approve the validity of the algorithm.

关键词： Membership function feature selection architecture pruning artificial neural networks

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Extraction of tree height from large viewing angle aerial images

Extraction of tree height from large viewing angle aerial im...

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International Conference on Space Information Technology

作者： Li, Chaoyang Yan, Guangjian Liu, Qiang Xiao, Zhiqiang Wang, Jingdi Laboratory of Pattern Recognition and Intelligent System School of Information Engineering Beijing University of Posts and Telecommunications 86-10-58809966 China State Key Laboratory of Remote Sensing Science Beijing Normal University Institute of Remote Sensing Applications Research Center for Remote Sensing School of Geography Beijing Normal University

ISBN: (纸本)0819460079

Due to the complexity and non-regularity of tree shapes, traditional digital photogrammetry using stereo matching method is difficult to obtain the accurate tree height, This fact therefore limits the application of the aerial digital photogrammetry technology in the power line survey. This paper presents a method of tree height extraction from large viewing aerial image using the knowledge of segmented tree crown. This method is based on a rough digital surface model (DSM) of tree crowns and the exterior orientation of the image. The basic steps of this method is that the DSM is first used to find the region of interest in the image based on the exterior orientation, and then the edges of the distinct trees or branches are extracted using image segmentation technology. An algorithm that uses both the rough DSM height information and exterior orientation data to calculate the accurate heights of the segmented trees or branches is presented. The algorithm assumes that most of the trees are upright, and the projection in the large viewing angle images of the crown and branches can therefore be used to calculate their heights relative to the averaged DSM height. Hence, the accurate height of the trees around the rough DSM can be refined. Some experimental results are given with the image captured from multi-angular imaging system mounted on a helicopter in which a Position and Orientation system (POS) is onboard to record the exterior element of the cameras. The experimental results demonstrated that this algorithm can largely improve the accuracy of tree height extraction. The application in power line monitoring system is promising.

关键词： Image processing

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Camera Abnormal Movement and Foreign Object Invasion Detection Based on Cumulative Edge Distribution Probability Model

Camera Abnormal Movement and Foreign Object Invasion Detecti...

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2018 International Conference on Security, pattern Analysis, and Cybernetics, SPAC 2018

作者： Yu, Xiangru Cai, Fudong Dou, Yimin Li, Jinping Institute of Pattern Recognition and Intelligent System School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan China Shandong College University Key Laboratory of Information Processing and Cognitive Computing in 13th Five-year University of Jinan Jinan China Shandong Senter Electronic Co. Ltd Zibo China

ISBN: (纸本)9781728105512

In practice, there often exist some occasions where video surveillance can only be realized by using rechargeable batteries due to the high cost of power supply. In order to extend the battery life, images can only be taken at a certain interval. Obviously, image difference is an important method to obtain various changes in this case. Among these changes, foreign invasion is one of the focuses. However, due to bolt shedding, abnormal weather and other factors, the camera may have abnormal movement which may seriously affect the detection effect of image difference method. Therefore, it is an urgent issue to find an effective way to detect the abnormal movement of camera and improve the detection accuracy of foreign invasion. Considering the characteristics of this kind of image sequences, we propose an effective algorithm to detect the camera abnormal movement and foreign object invasion based on a cumulative edge distribution probability model. Since sky region is relatively simple, we only discuss changes in sky region to detect camera abnormal movement. Our algorithm has 6 basic steps: firstly, segment the sky region;secondly, extract the edge information of the current image and the preceding adjacent image in the image sequence;thirdly, determine if the edge information of two adjacent images coincide. If consistent, then go to the next step, otherwise, it indicates that the camera has abnormal movement, then alarm;fourthly, calculate the cumulative edge probability distribution model in the sky region by using the historical image sequence;fifthly, by using adaptive Parzen window, determine if foreign object invasion exists by comparing the probability model of cumulative edge distribution with edge distribution of the current image;sixthly, update the cumulative edge distribution probability model in sky region. The algorithm achieves good results in practical applications. Through the test of thousands of images taken in the wild, the detection accuracy of

关键词： Cameras

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Fitting a functional structural plant model based on global sensitivity analysis

Fitting a functional structural plant model based on global ...

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2012 IEEE International Conference on Automation Science and Engineering: Green Automation Toward a Sustainable Society, CASE 2012

作者： Lin, Yubin Kang, Mengzhen Hua, Jing National Key Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781467304283

Calibration of a functional structural plant model is a challenging task because of the complexity of model structure. Parameter estimation through gradient-based optimization technique was highly dependent on initial parameter values. This motivated the use of global sensitivity analysis technique to choose parameter subset in fitting the data sequence. Global sensitivity indices were computed using the source sink ratio as the output of interest, which regulates all organ growth. By fitting on chrysanthemum data from nine sampling dates, it is shown that sensitivity analysis method helps to identify the influential parameters for a given sampling date. As a result, fitting process is less dependent on the initial parameter values. Current work provides a new method of calibrating a plant growth model with multiple outputs. © 2012 IEEE.

关键词： Sensitivity analysis

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Improved RRT algorithm path planning combined with artificial potential field algorithm 11

Improved RRT algorithm path planning combined with artificia...

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2021 11th International Workshop on Computer Science and Engineering, WCSE 2021

作者： Wang, Xiufen Yang, Shengyi School of Mechanical Electronic Engineering Guizhou Minzu University Guizhou Guiyang550025 China Key Laboratory of Pattern Recognition and Intelligent Systems of Guizhou Province Guizhou Minzu University Guizhou Guiyang550025 China

ISBN: (纸本)9789811817915

In order to solve the problem of low path planning efficiency in complex obstacle environment, an improved Rapidly-exploring Random Trees (RRT) algorithm is proposed. It utilizes artificial potential field to guide the fast expanding random tree to growing towards the target and away from obstacles. Considering the gravitational field of the target node and the repulsion field of the obstacle in the artificial potential field, a certain number of random nodes generated in one iteration are evaluated and selected. The simulation results show that the improved RRT algorithm has strong advantages over the basic RRT algorithm in search ability and computation time. © 2021 11th International Workshop on Computer Science and Engineering, WCSE 2021. All Rights Reserved.

关键词： Motion planning

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