Please wait a minute...
New Technology of Library and Information Service  2011, Vol. 27 Issue (5): 42-48    DOI: 10.11925/infotech.1003-3513.2011.05.07
Current Issue | Archive | Adv Search |
Design and Application of Distributed Image Retrieval Based on Color Model to Histogram Conversion
Cheng Xiufeng1, Zhu Song2, Xia Lixin1
1. Department of Information Management, Huazhong Normal University, Wuhan 430079,China;
2. Center of Computing & Experimenting,South-Central University for Nationalities, Wuhan 430074,China
Download: PDF(1240 KB)   HTML  
Export: BibTeX | EndNote (RIS)      
Abstract  The retrieval efficiency and the retrieval capability are considered as two major problems existing in CBIR systems. In order to improve the retrieval efficiency,the authors present a new CBIR application based on large databases in distributed environment using DHCIR (Distributed Image Retrieval method based on Color Model to Histogram Conversion) algorithm by reviewing past researches in CBIR and distributed computing. A new image retrieval system using this method is also developed. The test results show this application can provide stable, fast and efficient image retrieval functions to improve the retrieval speed and accuracy.
Key wordsHistogram      Color space      Content-based      Image retrieval      Distribution     
Received: 21 April 2011      Published: 11 July 2011
: 

G354

 

Cite this article:

Cheng Xiufeng, Zhu Song, Xia Lixin. Design and Application of Distributed Image Retrieval Based on Color Model to Histogram Conversion. New Technology of Library and Information Service, 2011, 27(5): 42-48.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2011.05.07     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2011/V27/I5/42

[1] Eakins J, Graham M. Content-based Image Retrieval . JISC Technology Applications Programme Report, 1999.

[2] Salton G, Buckley C. Term Weighting Approaches in Automatic Text Retrieval[J]. Information Processing and Management,1988, 24(5): 513-523.

[3] Arkin E M, Chew L P, Huttenlocher D P, et al. An Efficiently Computable Metric for Comparing Polygonal Shapes[J].IEEE Transactions on Pattern Analysis and Machine Intelligence Archive,1991,13(3):209-216.

[4] Huang T S, Mehratra S, Ramchandran K. Multimedia Analysis and Retrieval System (MARS) Project [J].Journal of VLSI Signal Processing,1998,20(1-2):137-150.

[5] Pentland A, Picard R W,Sclaroff S. Photobook: Content-based Manipulation of Image Databases[J]. International Journal of Computer Vision, 1996, 18(3):233-254.

[6] Wilensky R .The UC Berkeley Digital Library Project: Re-thinking Scholarly Information Dissemination and Use . In: Proceedings of the 3rd European Conference on Research and Advanced Technology for Digital Libraries.1999:853-854.

[7] Smith J R, Chang S F. VisualSeek: A Fully Automated Content-based Image Query System . In: Proceedings of the 4th ACM International Conference on Multimedia.1996:87-98.

[8] Yu C C, Jou F D, Lee C C,et al. Efficient Multi-resolution Histogram Matching for Fast Image/Video Retrieval[J]. Pattern Recognition Letters, 2008, 29(13): 1858-1867.

[9] Pan X, You Q, Liu Z, et al. 3D Shape Retrieval by Poisson Histogram[J]. Pattern Recognition Letters, 2011, 32(3): 787-794.

[10] Swain M J, Ballard D H. Color Indexing[J]. International Journal of Computer Vision, 1991,7(1):11-32.

[11] Levine B G, Stone J E, Kohlmeyer A. Fast Analysis of Molecular Dynamics Trajectories with Graphics Processing Units—Radial Distribution Function Histogramming[J]. Journal of Computational Physics, 2011, 230(9):3556-3569.

[12] Quellec G, Lamard M, Cazuguel G, et al. Wavelet Optimization for Content-based Image Retrieval in Medical Databases Original Research Article[J].Medical Image Analysis, 2010, 14 (2): 227-241.

[13] Phan R, Androutsos D. Content-based Retrieval of Logo and Trademarks in Unconstrained Color Image Databases Using Color Edge Gradient Co-occurrence Histograms[J]. Computer Vision and Image Understanding, 2010,114(1): 66-84.

[14] Han J, Ma K K. Fuzzy Color Histogram and Its Use in Color Image Retrieval[J].IEEE Transactions on Image Processing, 2002,11 (8):944-952.

[15] Park J, An Y, Kang G, et al. Defining a New Feature Set for Content-Based Image Analysis Using Histogram Refinement[J]. International Journal of Imaging Systems and Technology, 2008,18 (2-3): 86-93.

[16] Lin S D, Chen K, Yang X. Image Indexing by Color Plane Moment[J]. International Journal of Imaging Systems and Technology, 2002,12(4):139-148.

[17] Mejdoub M, Fonteles L, BenAmar C, et al. Embedded Lattices Tree: An Efficient Indexing Scheme for Content Based Retrieval on Image Databases[J].Journal of Visual Communication and Image Representation, 2009,20(2): 145-156.

[18] Liu G H, Zhang L, Hou Y K,et al. Image Retrieval Based on Multi-text on Histogram[J]. Pattern Recognition, 2010,43 (7): 2380-2389.

[19] Brunelli R, Mich O. Histograms Analysis for Image Retrieval[J].Pattern Recognition, 2001,34(8):1625-1637.

[20] Efford N. Digital Image Processing: A Practical Introduction Using Java[M]. New Jersey: Addison Wesley, 2000.

[21] Cowlishaw M F. Fundamental Requirements for Picture Presentation[J]. Proceedings of the Society for Information Display,1985, 26(2): 101-107.

[22] Strelkov V V. A New Similarity Measure for Histogram Comparison and Its Application[J]. Pattern Recognition Letters, 2008,29(13):1768-1774.

[23] 何楚,王思贤,廖孟扬.基于内容的图像搜索的算法模型与分布式方案[J] . 小型微型计算机系统, 2002,23(5): 544-547.

[24] Stallings W. Computer Organization and Architecture: Designing for Performance[M]. Columbus, Ohio: Prentice Hall, 2006.
[1] Ke Li,Yuya Sasaki. Analyzing Sentiment Distribution with Spatial-textual Data of Multi-dimensional Clustering[J]. 数据分析与知识发现, 2019, 3(7): 14-22.
[2] Zhuchen Liu,Hao Chen,Yanhua Yu,Jie Li. Extracting Keywords with TextRank and Weighted Word Positions[J]. 数据分析与知识发现, 2018, 2(9): 74-79.
[3] Ling Wang,Qianjin Dai,Xiaojun Wu. The Study on the Temporal and Spatial Distribution of Event Tourism Based on Large-scale Tourism Early Warning Platform[J]. 数据分析与知识发现, 2018, 2(8): 31-40.
[4] Bo Guo,Junrui Zhao,Yu Sun. Analyzing Characteristics and Dynamics of User Behaviors in Social Q&A Community: Case Study of Zhihu.com[J]. 数据分析与知识发现, 2018, 2(4): 48-58.
[5] Qu Yunpeng,Wang Wenling. Using Semantic Model to Build Lexical Chains[J]. 现代图书情报技术, 2016, 32(9): 34-41.
[6] Wang Zhongqun, Huang Subin, Xiu Yu, Zhang Yi. Research on Metrics-Model for Online Product Review Depth Based on Domain Expert and Feature Concept Tree of Products[J]. 现代图书情报技术, 2015, 31(9): 17-25.
[7] Li Xiangdong, He Haihong, Cao Huan, Huang Li. An Algorithm of Digital Resources Text Categorization for Training Sets Skewed Distribution[J]. 现代图书情报技术, 2014, 30(7): 24-33.
[8] Wu Kun, Xie Xiaqing, Bai Quanwei, Wu Xu. Implementation and Application of Image Retrieval Technology in “Classic Reading” Teaching System[J]. 现代图书情报技术, 2014, 30(5): 90-95.
[9] Li Xiangdong, Ba Zhichao, Huang Li. A Method for Eliminating Noise in Text Classification Based on Category Distribution Characteristics[J]. 现代图书情报技术, 2014, 30(11): 66-72.
[10] He Jing, Guo Jinli, Xu Xuejuan. Analysis on Statistical Characteristic and Dynamics for User Behavior in Microblog Communities[J]. 现代图书情报技术, 2013, 29(7/8): 94-100.
[11] Hu Bing, Zhang Jianli. Research on Chinese Patent Automatic Classification Method Based on Statistical Distribution[J]. 现代图书情报技术, 2013, 29(7/8): 101-106.
[12] Ai Danxiang, Zuo Hui, Yang Jun. Research on Three-dimensional Personalized Recommendation Approach for C2C E-commerce Platform[J]. 现代图书情报技术, 2013, 29(1): 36-42.
[13] Fang Naiwei, Lv Xueqiang, Zhang Dan. Mechanical Design Image Retrieval with Combined Geometrical Features[J]. 现代图书情报技术, 2013, 29(1): 43-49.
[14] Zhang Huiying, Xue Fuliang. An Improved Collaborative Filtering Recommendation Algorithm Based on Vague Sets Theory[J]. 现代图书情报技术, 2012, 28(3): 35-39.
[15] Zhang Wanting, Wang Bin. Design of Online System for Trademark Retrieval Based on Composite Features[J]. 现代图书情报技术, 2011, 27(9): 41-45.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn