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CBIR System using Color Moment and Color Auto-Correlogram with Block Truncation Coding

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Vandana Vinayak, Sonika Jindal

Vandana Vinayak and Sonika Jindal. CBIR System using Color Moment and Color Auto-Correlogram with Block Truncation Coding. International Journal of Computer Applications 161(9):1-7, March 2017. BibTeX

	author = {Vandana Vinayak and Sonika Jindal},
	title = {CBIR System using Color Moment and Color Auto-Correlogram with Block Truncation Coding},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {161},
	number = {9},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {1-7},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2017913282},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In content-based Image Retrieval (CBIR) application, a large amount of data is processed. Among various low-level features like color, shape and texture, color is an important feature and represented in the form of histogram. It is essential that features required to be coded in such a way that the storage space requirement is low and processing speed is high. In this paper, we propose a method for indexing of images in the large database with lossy compression technique known as Block Truncation Coding (BTC) along with two different color feature extraction methods - Color Moment and Color Auto-correlogram. Block truncation coding divided the original image into multiple non-overlapping blocks and then retrieve the required features. The proposed method performs better.


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CBIR, Color Moment, Color Auto-Correlogram, Block Truncation Coding