Color Image Indexing by Exploiting the Simplicity of the EDBTC Method

Abstract

This paper presents a novel approach called Error Diffusion Block Truncation Coding (EDBTC) to extract the texture and features of an image. Here, two methods are introduced such as Color Histogram Feature (CHF) and Bit Pattern Histogram Feature (BHF), to measure the similarity between the query image and the target image in database as well as to extract the features of an image. The EDBTC produces two color quantizers and a bitmap image which are further processed using Vector Quantization (VQ) to generate the image feature descriptor. As documented in experimental result, the proposed indexing method outperforms the former BTC-based image indexing and the other existing image retrieval schemes with natural and textural datasets