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2003-2020 全部
为您找到包含“Pattern recognition”的内容共476

Yu Jie,Zhang Honggang,Li Qiaohong,Chai Lunshao,Qi Yonggang

With the development of the 3G network and Electronic Commerce, more and more people prefer to shop online, especially via the Cell phone equipped with camera. In order to meet the requirements of the consumers to easily retrieve similar commodity images, we propose a Mobile Image-to-Search system. In this system a content-based retrieval algorithm combining color and shape features for electronic commerce has been investigated, which uses the Normalized Fourier Descriptor and a fuzzy-linking method of color histogram based on the HSV color space. In order to reduce the interference of background, we also use the method of improved canny descriptor before extracting the shape features and the approach of ROI (region of interest) weighted in the color histogram. The system has been tested on Corel data set and our own commodity library, a large number of images selected from Taobao, one of the largest Electronic Commerce web in China. The experimental results indicate that our method has a better retrieval performance.

2011-10-20

the Fundamental Research Funds for the Central Universities under Grant(No.2009RC0130

National Natural Science Foundation of China under Grant (No.61005004

Pattern Recognition and Intelligent System Lab,Beijing University of Posts and Telecommunications

#Computer Science and Technology#

0评论(0 分享(0)

Hu Mingyuan,Dai Yourui,Zhang Honggang

Extracting the license plate region is the critical first step in the license plate recognition system. This paper adopts grey level stretch and image enhancement to get better images. For locating the license plate in night scene, this paper proposes a lights searching method base on projection algorithm. Through rough location module, stretch location module, analysis module and three-level scoring system, the license plate will be extracted finally.

2011-08-25

Pattern Recognition Lab, School of Information and Communication Engineering, Beijing University of

#Computer Science and Technology#

0评论(0 分享(0)

Dai Yourui,ZhangHonggang,LiQiaohong

Benefit from the lower cost and the easier installation, Intelligent Traffic system (ITS) based on high definition (HD) picture is increasingly used. In this paper, we describe a edge and color feature based method, which is able to locate and extract license plate from the high definition images in real-time. In the proposed algorithm, the edge feature is fully utilized to find the candidate region of the license plate (LP). And then, a edge identity similarity method is employed to adjust the position of each candidate, which can get the accurate LP position. Finally, an effective evaluation method is proposed to get the real LP from the candidate region. This thoroughly integrated system can obtain accurate localization of LP real-time in the HD traffic pictures under complicated background and changing illumination conditions. The experiment results indicate that the presented system is excellent in accuracy with a good speed.

2011-12-23

Pattern Recognition Lab, School of Information and Communication Engineering, Beijing University of

#Electrics, Communication and Autocontrol Technology#

0评论(0 分享(0)

赵磊

2008-12-18

模式识别(Pattern Recognition)是人类的一项基本智能,在日常生活中,人们经常在进行“模式识别”。随着20世纪40年代计算机的出现以及50年代人工智能的兴起,人们当然也希望能

辽宁工程技术大学理学院

#数学#

1评论(0 分享(0)

Zhang Meng,Zhang Honggang,Chai Lunshao,Li Qiaohong

Key frame extraction is one of the basic procedures in video retrieval. Key frame extraction aims at finding a small collection of image frame sequences extracted from a video sequence in order to reduce the amount of data that must be examined. Efficient key frame extraction techniques will facilitate the video browsing systems, which have wide applications in real world. In this paper, we proposed an innovative approach to the selection of key frames of a video sequence. First, two descriptors of color and edge features are used to describe visual content, and are integrated as a muti-feature descriptor, then we analyze the differences between two consecutive frames of a video sequence. Finally, key frames are extracted by the dynamic threshold algorithm. Experimental results show that the proposed algorithm can dynamically and rapidly select a variable number of key frames within each sequence and can achieve high compression ratio and high fidelity.

2012-01-06

Fundamental Research Funds for the Central Universities under Grant(No.2009RC0130

National Natural Science Foundation of China under Grant(No.61005004

Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications

#Electrics, Communication and Autocontrol Technology#

0评论(0 分享(0)

李茜,任珊,刘鑫

2009-09-25

模式识别(Pattern Recognition)是人类的一项基本智能,在日常生活中,人们经常在进行“模式识别”。在社会生活和生产实践中,人们很容易用语言来描述事物的特点、模式的特征,根据人类语言的

辽宁工程技术大学理学院,辽宁工程技术大学理学院,辽宁工程技术大学理学院

#数学#

0评论(0 分享(0)

Chao Ma, Yun Gu, Wei Liu, Jie Yang, Xiangjian He

Video hashing is a common solution for content-based video retrieval by encoding high-dimensional feature vectors into short binary codes. Videos not only have spatial structure inside each frame but also have temporal correlation structure between frames, while the latter has been largely neglected by many existing methods. Therefore, in this paper we propose to perform video hashing by incorporating the temporal structure as well as the conventional spatial structure. Specifically, the spatial features of videos are obtained by utilizing Convolutional Neural Network (CNN), and the temporal features are established via Long-Short Term Memory (LSTM). The proposed spatio-temporal feature learning framework can be applied to many existing unsupervised hashing methods such as Iterative Quantization (ITQ), Spectral Hashing (SH), and others. Experimental results on the UCF-101 dataset indicate that by simultaneously employing the temporal features and spatial features, our hashing method is able to significantly improve the performance of existing methods which only deploy the spatial feature.

2016-06-13

Ph.D. Programs Foundation of Ministry of Education of China (No.20120073110018

Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai

#Electrics, Communication and Autocontrol Technology#

0评论(0 分享(0)

孟德龙,苏志强

2015-02-02

receptors,TLRs)是先天性免疫系统最重要的模式识别受体( pattern recognition receptors,PRRs),在先天免疫和炎症中发挥着关键作用。本文就TLRs信号通路参与脑出血引起的

教育部高等学校博士点专项科研基金( 20122307110013

哈尔滨医科大学附属第一医院神经内科,哈尔滨,中国,哈尔滨医科大学附属第一医院神经内科,哈尔滨,中国。

#临床医学#

0评论(0 分享(0)

Xiayang Zhao,Jinshui Chen

Two methods can be used to measure water level. One is creating a water-level measuring post, then read it by human each time. Another one is using sensor to derive the analog water level, then transform it to digital value. There are many different sensors for water level measuring, such as float model, pressure model, supersonic model, etc. This paper provides a method that derives the image of water level by camera firstly, then by employing the methodology of image preprocessing, we can get the number of the calibrations above the water, in the end conduct the water level value. Using this method, the devices are easily to install, can save cost, and has high precision, so it is suitable to apply in irrigation district.

2007-02-01

College of Computer & Information Engineering, Hohai University, Nanjing, P. R. China,College of Computer & Information Engineering, Hohai University, Nanjing, P. R. China

#Computer Science and Technology#

陈璐,蒋争凡

2011-01-24

道防线,天然免疫系统通过机体的模式识别受体(pattern-recognition receptor, PRRs) 对病原相关分子模式(pathogen-associated molecular

高等学校博士学科点专项科研基金(20070001033

北京大学生命科学学院,北京大学生命科学学院

#生物学#

0评论(0 分享(0)