期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2010
卷号：2
期号：8
页码：2535-2544
出版社：Engg Journals Publications
摘要：The augmentation to block truncation coding (BTC) based image retrieval techniques using Even and Odd images with ten different colour spaces is the theme of work given in the paper. Here the original image is reflected across vertical axis to obtain the flip image, then even and odd images are obtained respectively by addition of original with flip and subtraction of flip from original. The BTC is applied on original image, even image and odd image to get seven different combinational feature sets for content based image retrieval (CBIR) techniques like original, even, odd, original & even, original & odd, even & odd and original & even & odd. Use of ten sundry colour spaces results into total seventy CBIR methods, For experimentation the generic image database having 1000 images spread across 11 categories is used. For each proposed CBIR technique 55 queries (5 per category) are fired on the generic image database. To compare the performance of image retrieval techniques average precision and recall are computed of all queries. The results have shown the performance improvement (higher precision and recall values) with these proposed colour- BTC methods. Instead of using just 6 feature vector in BTC, if we perform the image retrieval using the flipping technique wherein the feature vector is increased to 12 and 18,the performance also increases except in the case of normalized rgb colour space. Image flipping helps to improve the performance in all of luminance-chromaticity colour spaces (YUV, YIQ, LUV, Kekre�s YCgCb, YCbCr) as well as non-luminance based colour spaces (XYZ,HSI,RGB,HSV) in comparison of BTC applied on original image. Also overall YUV colour space proves to be the best in all colour spaces for proposed image flipping techniques. The second best performance is given by Kekre�s YCGCb colour space.
