Hybrid feature to encode shape and texture for Content Based Image Retrieval
Inhaltsverzeichnis
Referenz
Rai, H.G.N.; Xiaobo Shen; Deepak, K.S.; Krishna, P.R.: Hybrid feature to encode shape and texture for Content Based Image Retrieval. Image Information Processing (ICIIP), 2011 International Conference on , pp.1-6, 3-5 Nov. 2011
DOI
http://dx.doi.org/10.1109/ICIIP.2011.6108971
Abstract
In this paper, we propose an approach for representing both shape and texture information in an image using a single hybrid feature descriptor for Content Based Image Retrieval. Towards this, we compute the gradient magnitude of the input image prior to deriving features. Feature extraction is then performed using the responses from a bank of Gabor filters. Here, we exploit the fact that shape corresponds to the high spatial frequency content in the image whereas natural texture information predominantly lies within low to mid-range frequencies. This approach helps in better localization of characteristic texture as well as shape, due to spread of energy towards high frequencies in spectral domain. Moment invariants are extracted from Gabor filter responses which yield better retrieval performance than conventional statistical features. Experimental results show that this approach has relatively improved retrieval performance on Corel image data set when compared with recent approaches in the literature. Further experiments were also performed on a medical image dataset with 95.4 percent precision and 74.6 percent recall.
Extended Abstract
Bibtex
@INPROCEEDINGS{6108971,
author={H. G. N. Rai and Xiaobo Shen and K. Sai Deepak and P. Radha Krishna},
booktitle={Image Information Processing (ICIIP), 2011 International Conference on},
title={Hybrid feature to encode shape and texture for Content Based Image Retrieval},
year={2011},
pages={1-6},
keywords={Gabor filters;content-based retrieval;feature extraction;image retrieval;image texture;Gabor filters;content based image retrieval;feature extraction;medical image dataset;moment invariants;shape information representation;single hybrid feature descriptor;texture information representation;Feature extraction;Image retrieval;Industries;Medical diagnostic imaging;Medical services;Shape;Content based image retrieval;Feature extraction;Gabor wavelet;Shape;Texture},
doi={10.1109/ICIIP.2011.6108971},
url={http://dx.doi.org/10.1109/ICIIP.2011.6108971 http://de.evo-art.org/index.php?title=Hybrid_feature_to_encode_shape_and_texture_for_Content_Based_Image_Retrieval },
month={Nov},
}
Used References
W. Chowattanakul, H. G. N. Rai, and P. R. Krishna, "An efficient shape based feature for retrieval of healthcare literatures using CBIR technique," in Proceedings of the Fourth Annual ACM Bangalore Conference, ser. COMPUTE '11. ACM, 2011, pp. 24:1-24:4. http://dx.doi.org/10.1145/1980422.1980446
A. Oliva and A. Tonalba, "Modeling the shape of the scene: a holistic representation of the spatial envelope," International Journal of Computer Vision, vol. 42, no. 3, pp. 145-175, 2001. (Pubitemid 32680801) http://dx.doi.org/10.1023/A:1011139631724
O. Mori, S. Belongie, and J. Malik, "Efficient shape matching using shape cnntexts," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 11, pp. 1832-1837, 2005. (Pubitemid 41685118) http://dx.doi.org/10.1109/TPAMI.2005.220
B. Manjunath and W. Ma, "Texture features for browsing and retrieval of image data," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 8, pp. 837-842, 1996. (Pubitemid 126772825) http://dx.doi.org/10.1109/34.531803
S. Thangam, K. Deepak, H. G. N. Rai, and P. Mirajkar, "An effective edge detection methodology for medical images based on texture discrimination," in Seventh International Conference on Advances in Pattern Recognition, 2009. ICAPR '09., feb 2009, pp. 227-231. http://dx.doi.org/10.1109/ICAPR.2009.44
N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005. CVPR 2005., vol. 1, jun 2005, pp. 886-893. http://dx.doi.org/10.1109/CVPR.2005.177
H. Abrishami Moghaddam and M. Saadatmand-Tarzjan, "Gabor wavelet conelogram algorithm for image indexing and retrieval," in 18th International Conference on Pattern Recognition, 2006. ICPR 2006., vol. 2, sep 2006, pp. 925-928. http://dx.doi.org/10.1109/ICPR.2006.593
A. B. Gonde, R. P. Maheshwari, and R. Balasubramanian, "Rotated complex wavelet transform with vocabulary tree for content based image retrieval," in Proceedings of the First International Conference on Intelligent Interactive Technologies and Multimedia, ser. IITJVI '10. New York, NY, USA: ACM, 2010, pp. 284-291. [Online]. Available: http://doi.acm.org/10.1145/1963564.1963614
M. Eisa, M. Refaat, and A. F El-Gamal, "Preliminary diagnostics of mammograms using moments and texture features," ICGST-G VIP Journal, vol. 9, no. 5, pp. 21-27, 2009.
A. Ahmadian, E. Faramarzi, and Sayadian, "Image indexing and retrieval using gabor wavelet and legendre moments," in Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE, vol. 1, sep 2003, pp. 560-563. http://dx.doi.org/10.1109/IEMBS.2003.1279806
R. Choras, "Iris-based person identification using gabor wavelets and moments," in Biometrics and Kansei Engineering, 2009. ICBAKE 2009. International Conference on, jun 2009, pp. 55-59. http://dx.doi.org/10.1109/ICBAKE.2009.21
S. Wang and Y. Xu, "A new palmprint identification algorithm based on gabor filter and moment invariant," in Cybernetics and Intelligent Systems, 2008 IEEE Conference on, sep 2008, pp. 491-496. http://dx.doi.org/10.1109/ICCIS.2008.4670743
M.-K. Hu, "Visual pattern recognition by moment invariants," Information Theory, IRE Transactions on, vol. 8, no. 2, pp. 179-187, 1962. http://dx.doi.org/10.1109/TIT.1962.1057692
J. Flusser, "On the independence of rotation moment invariants," Pattern Recognition, vol. 33, pp. 1405-1410, 2000. http://dx.doi.org/10.1016/S0031-3203(99)00127-2
Links
Full Text
