Image Retrieval Based on the Characteristics of Concentric Circular Regions

Zhong Sheng Li; Tong Cheng Huan; Xu Dong Li; Xiao Lu Tian

doi:10.4028/www.scientific.net/AMM.519-520.594

Paper Titles

Study of Fingerprint Image Feature Extraction Algorithm
p.577

Study of Fingerprint Image Preprocessing Technology
p.581

Spatial Topological Relationship for Remote Sensing Image Analysis
p.585

Overview of Pixel Level Image Fusion Algorithm
p.590

Image Retrieval Based on the Characteristics of Concentric Circular Regions
p.594

A Fast Extraction Method of Water Boundary Based on the Landsat TM Image
p.598

A New Perspective Shape from Shading Approach for Hybrid Surfaces
p.602

Non-Western Script Based Off-Line Handwritten Signature Technology: A Survey
p.606

Research of Computer-Aided Diagnosis about Pulmonary Interstitial Pathology Based on Wavelet Decomposition
p.611

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 519-520Image Retrieval Based on the Characteristics of...

Image Retrieval Based on the Characteristics of Concentric Circular Regions

Abstract:

Color is one of the important characteristics in visual perception. But color histograms used commonly loses spatial distribution information while obtains the statistical feature of image color. This paper provides an algorithm, the region partitioning algorithm based on concentric circles, that synthesizes the color, texture and space information to extract features of image. It evidently improves the precision of retrieval and achieve better performance.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 519-520)

Pages:

594-597

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.519-520.594

Citation:

Cite this paper

Online since:

February 2014

Authors:

Zhong Sheng Li*, Tong Cheng Huan, Xu Dong Li, Xiao Lu Tian

Keywords:

CBIR, Color, Overlapped Block Algorithm, Region Partitioning Algorithm Based on Concentric Circles, Space

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] S. K. Chang, C. W. Yan, D. C. Dimitroff. An intelligent image database system. IEEE Trans. on Software Eng. 14(5): 412-421 (1998).

Google Scholar

[2] R. Datta ,D. Jnshi, J. Li , et al. Image Retrieval: Ideas, Influences, and Trends of the New Age. ACM Computing Surveys. 40(2): l一60 (2008).

DOI: 10.1145/1348246.1348248

Google Scholar

[3] A Pentland, R Picard, S Sclaroff. Photobook: Content-Based Manipulation of Image Databases. SPIE Storage and Retrieval for Image and Video Databases H[C]. 34-47(1994).

DOI: 10.1117/12.171786

Google Scholar

[4] Yong Rui, Thomas S Huang, Shih-Fu Chang. Image Retrieval: Part, Present, and Future[J]. Journal of Visual Communication and Image Representation, 10(1): 39-62(1998).

Google Scholar

[5] Yoo Hun-Woo, Jung She-Hwan. Extraction of Major Object Feature Using VQ Clustering for Content-based Image Retrieval. Pattern Recognition. 835(2): 1115-1126(2002).

DOI: 10.1016/s0031-3203(01)00105-4

Google Scholar

[6] Lin Hwei-Jen, Kao Yang-Ta. A Study of Shape-based Image Retrieval. IEEE Computer. 22(2): 645-662. (2004).

DOI: 10.1109/icdcsw.2004.1284018

Google Scholar

[7] Yu Honpug-Heather. Visual Image Retrieval on Compressed Domain with Q-Distance Image Signal Process. International Journal of Computer Vision. 31(1): 134-149. (2000).

Google Scholar