A Survey: Content Based Image Retrieval using Block Truncation Coding

Vipul R. Mahajan, Alka Khade

Abstract


A new approach to index color images using the features extracted from the error diffusion Block truncation coding (EDBTC). The EDBTC produces two color quantizes and a bitmap Image, which is further, managed using vector quantization (VQ) to create the image feature Descriptor. Herein two features are presented namely, colour histogram feature (CHF),bit Pattern histogram feature (BHF) to measure the similarity between a query image and the Target image in database. The CHF and BHF are calculated from the VQ-indexed color quantized and VQ- indexed bitmap image, respectively. The distance calculated from CHF and BHF can be utilized to measure the similarity between two images. A new approach to index colour images using the features extracted from the error diffusion Block truncation coding (EDBTC). The EDBTC produces two colour quantizes and a bitmap Image, which is further, managed using vector quantization (VQ) to create the image feature Descriptor. Herein two features are presented namely, color histogram feature (CHF),bit Pattern histogram feature (BHF) to measure the similarity between a query image and the Target image in database. The CHF and BHF are calculated from the VQ-indexed color quantized and VQ- indexed bitmap image, respectively. The distance calculated from CHF and BHF can be utilized to measure the similarity between two images.

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References


G. Qiu, “Color image indexing using BTC,” IEEE Trans. Image Process., vol. 12, no. 1, pp. 93–101, Jan. 2003.

M. R. Gahroudi and M. R. Sarshar, “Image retrieval based on textureand color method in BTC-VQ compressed domain,” in Proc. Int. Symp. Signal Process. Appl., Feb. 2007, pp.1-4.

F.-X. Yu, H. Luo, and Z.-M. Lu, “Colour image retrieval using pattern co-occurrence matrices based on BTC and VQ,” Electron. Lett., vol. 47,no. 2, pp. 100–101, Jan. 2011.

S. Silakari, M. Motwani, and M. Maheshwari, “Color image clustering using block truncation algorithm,” Int. J. Comput. Sci. Issues, vol. 4, no. 2, 2009, pp. 31–35.

Z.-M. Lu and H. Burkhardt, “Colour image retrieval based on DCT-domain vector quantisation index histograms,” Electron. Lett., vol. 41, no. 17, pp. 956–957, 2005.

P. Poursistani, H. Nezamabadi-Pour, R. A. Moghadam, and M. Saeed, “Image indexing and retrieval in JPEG compressed domain based on vector quantization,” Math. Comput. Model., vol. 57, nos. 5–6, pp. 1005–1017, 2013. [Online]. Available: http://dx.doi.org/10.1016/j.mcm.2011.11.064

M. E. ElAlami, “A novel image retrieval model based on the most relevant features,” Knowl.-Based Syst., vol. 24, no. 1, pp. 23–32, 2011.

J.-M. Guo, H. Prasetyo, and H.-S. Su, “Image indexing using the color and bit pattern feature fusion,” J. Vis. Commun. Image Represent., vol. 24, no. 8, pp. 1360–1379, 2013.

E. J. Delp and O. R. Mitchell, “Image compression using block truncation coding,” IEEE Trans. Commun., vol. 27, no. 9, pp. 1335–1342, Sep. 1979.

] Y.-G. Wu and S.-C. Tai, “An efficient BTC image compression tech-nique,” IEEE Trans. Consum. Electron., vol. 44, no. 2, pp. 317–325, May 1998.

J.-M. Guo and Y.-F. Liu, “Joint compression/watermarking scheme using majority-parity guidance and halftoning-based block truncation coding,”IEEE Trans. Image Process., vol. 19, no. 8, pp. 2056–2069, Aug. 2010.

J.-M. Guo, “Improved block truncation coding using modified error diffusion,” Electron. Lett., vol. 44, no. 7, Mar. 2008, pp. 462–464.

J.-M. Guo, S.-C. Pei, and H. Lee, “Watermarking in halftone images with parity-matched error diffusion,” Signal Process., vol. 91, no. 1, pp. 126–135, 2011

S.-C. Pei and J.-M. Guo, “Hybrid pixel-based data hiding and block-based watermarking for error-diffused halftone images,” IEEE Trans. Circuits Syst. Video Technol., vol. 13, no. 8, pp. 867–884, Aug. 2003.

Y. F. Liu, J. M. Guo, and J. D. Lee, “Halftone image classification using LMS algorithm and naive Bayes,” IEEE Trans. Image Process., vol. 20, no. 10, pp. 2837–2847, Oct. 2011

Y.-F. Liu, J.-M. Guo, and J.-D. Lee, “Inverse halftoning based on the Bayesian theorem,” IEEE Trans. Image Process., vol. 20, no. 4, pp. 1077–1084, Apr. 2011.

J.-M. Guo and Y.-F. Liu, “High capacity data hiding for error-diffused block truncation coding,” IEEE Trans. Image Process., vol. 21, no. 12,pp. 4808–4818, Dec. 2012.

] J.-M. Guo and Y.-F. Liu, “Halftone-image security improving using overall minimal-error searching,” IEEE Trans. Image Process., vol. 20, no. 10, pp. 2800–2812, Oct. 2011.

Color Image Clustering using Block Truncation Algorithm IJCSI International Journal of Computer Science Issues, Vol. 4, No. 2, 2009

HSV Color Motif Co-Occurrence Matrix for Content based Image Retrieval International Journal of Computer Applications (0975 – 888) Volume 48– No.16, June 2012

Enhancement Image Compression Using BTC Algorithm Volume 4, Issue 2, February 2014 ISSN: 2277 128X

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DOI: https://doi.org/10.23956/ijarcsse.v7i12.495

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