Image Retrieval by using histogram equalization and DBTCF using SVM

Abstract

Retrieving images as of from vast quantity of database which is based on to their content are being
recognized content based image retrieval. Efficiency of any CBIR system is depend on features mined to stand for an
image. As a outcome feature extraction is crucial step in design and the development of some CBIR. Most normally used
features to signify images are Color, texture and shape. Here the Block truncation coding feature known as (BTCF) is
used so as to compress the image. Further it give thought of Support Vector Machine also known (SVM) classifier. In
paper the block of data is also divided into different chunks, so that image of single instance can be stored in these
chunks. So replication will be enhanced with the aid of compression techniques which is discussed in detail. Here basic
CBIR system is being developed by the combine features like color correlogram , color moments and Gabor wavelet
transform all along by way of histogram descriptor. Further outcome is being obtained are then compared through
CBIR system is using the SVM classifier