Image retrieval using Block Truncation Coding Extended to Color Clumps

Author

Kekre, H.B. ; Thepade, Sudeep D. ; Lohar, A.T.

Author_Institution

Dept. of Comput. Eng., SVKM´s NMIMS, Mumbai, India

fYear

2013

fDate

23-25 Jan. 2013

Firstpage

1

Lastpage

6

Abstract

Image retrieval is useful to retrieve images from outsized image databases, which can be beneficial to plenty of image supporting applications. Colors of an image are easier for extraction. Block Truncation Coding (BTC) prominently used with many variations. This paper proposed a novel Block Truncation Coding Extended to Color Clumps for image retrieval purpose. Total of 24 variations, using four clumps and six color spaces are experimented on image database having 1000 images. Experimental results have shown better performance in YCbCr color space followed by YUV and LUV. The best image retrieval is by Extended Block truncation coding using 8 color clumps in YCbCr color space.

Keywords

block codes; image colour analysis; image retrieval; visual databases; BTC; Extended Block truncation coding; LUV; YUV; color clump; image retrieval purpose; image supporting application; outsized image databases; Equations; Image color analysis; Image retrieval; Manganese; Mathematical model; Vectors; BTC; Color Clump; Even Odd BTC; Extended BTC; Image Retrieval (IR); LUV; Multilevel BTC; YCbCr; YCgCb; YIQ; YUV;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Technology and Engineering (ICATE), 2013 International Conference on

Conference_Location

Mumbai

Print_ISBN

978-1-4673-5618-3

Type

conf

DOI

10.1109/ICAdTE.2013.6524769

Filename

6524769