An edge-based color image retrieval by using multiple features

Moshi Shibie yu Rengong Zhineng/Pattern Recognition and Artificial Intelligence

Volumn 23, Issue 2, 2010, Pages 216-221

  Wang, Xiang Yang ^a,b   Chen, Jing Wei ^a   Yu, Yong Jian ^a  

^a LIAONING NORMAL UNIVERSITY   (China)

^b NANJING UNIVERSITY   (China)

Author keywords

Angle histogram; Color edge; Gradient orientation histogram; Image retrieval; Weighted color histogram

Indexed keywords

ANGLE HISTOGRAMS; COLOR EDGE; COLOR EDGES; COLOR HISTOGRAM; COLOR IMAGE RETRIEVAL; COLOR IMAGES; COMBINED FEATURES; CONTENT-BASED IMAGE RETRIEVAL; EDGE-BASED; GRADIENT ORIENTATIONS; IMAGE EDGE; IMAGE FEATURES; MULTIPLE FEATURES;

COLOR; COLOR IMAGE PROCESSING; CONTENT BASED RETRIEVAL; FEATURE EXTRACTION; GRAPHIC METHODS; INFORMATION RETRIEVAL;

STATISTICAL METHODS;

EID: 77953252113     PISSN: 10036059     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (19)

1. Datta R, Joshi D, Li Jia, et al. Image Retrieval: Ideas, Influences, and Trends of the New Age. ACM Computing Surveys, 2008, 40(2): 1-60
2. Michael S L, Nice S, Chababe D, et al. Content-Based Multimedia Information Retrieval: State of the Art and Challenges. ACM Trans on Multimedia Computing, Communications and Applications, 2006, 2(1): 1-19
3. Swain M J, Ballard D H. Color Indexing. International Journal of Computer Vision, 1991, 7(1): 11-32
4. Li Xuelong. Image Retrieval Based on Perceptive Weighted Color Blocks. Pattern Recognition Letters, 2003, 24(12): 1935-1941
5. Wang Yi, Zhai Hongchen, Liang Yanmei, et al. Shape Description Matrix and Its Applications to Color-Image Retrieval and Recognition. Science in China: Series E, 2004, 34(3): 337-344 (in Chinese)
6. Jeong S, Won C S, Gray R M. Image Retrieval Using Color Histograms Generated by Gauss Mixture Vector Quantization. Computer Vision and Image Understanding, 2004, 94(1/2/3): 44-66
7. Stöttinger J, Sebe N, Gevers T, et al. Colour Interest Points for Image Retrieval//Proc of the 12th Computer Vision Winter Workshop. Hubli, India, 2007: 83-90
8. Haralick R M, Shanmngam K, Dinstein I. Texture Feature for Image Classification. IEEE Trans on Systems, Man and Cybernetics, 1973, 3(6): 610-621
9. Tarmura H, Mori S, Yamawaki T. Texture Features Corresponding to Visual Perception. IEEE Trans on Systems, Man and Cybernetics, 1978, 8(6): 460-473
10. Manthalkar R, Biswas P K, Chatterji B N. Rotation and Scale Invariant Texture Features Using Discrete Wavelet Packet Transform. Pattern Recognition Letters, 2003, 24(14): 2455-2462
11. Kourosh J K, Hamid S Z. Rotation-Invariant Multiresolution Texture Analysis Using Radon and Wavelet Transform. IEEE Trans on Image Processing, 2005, 14(6): 783-795
12. Han Ju, Ma K K. Rotation-Invariant and Scale-Invariant Gabor Features for Texture Image Retrieval. Vision and Image Computing, 2006, 25(9): 1474-1481
13. Pun C M, Lee M C. Log-Polar Wavelet Energy Signatures for Rotation and Scale Invariant Texture Classification. IEEE Trans on Pattern Analysis and Machine Intelligence, 2003, 25(5): 590-603
14. Gluckman J. Visually Distinct Patterns with Matching Subband Statistics. IEEE Trans on Pattern Analysis and Machine Intelligence, 2005, 27(2): 252-264
15. Zhang Dengsheng, Lu Guojun. Review of Shape Representation and Description Techniques. Pattern Recognition, 2004, 37(1): 1-19
16. Xu Xiaoqian, Lee D J, Antani S, et al. A Spine X-Ray Image Retrieval System Using Partial Shape Matching. IEEE Trans on Information Technology in Biomedicine, 2008, 12(1): 100-108
17. Wei C H, Li Y, Chau W Y, et al. Trademark Image Retrieval Using Synthetic Features for Describing Global Shape and Interior Structure. Pattern Recognition, 2009, 42(3): 386-394
18. Hiremath P S, Pujari J. Content Based Image Retrieval Using Color, Texture and Shape Features//Proc of the 15th International Conference on Advanced Computing and Communications. Guwahati, India, 2007: 780-784
19. Canny J. A Computational Approach to Edge-Detection. IEEE Trans on Pattern Analysis and Machine Intelligence, 1986, 8(6): 679-698