This paper presents a new approach for compression and Retrieval. To index color images using the features extracted from the EDBTC it stands for error diffusion block truncation coding. The EDBTC produces a bitmap image and two color quantizers, which processed using vector quantization (VQ) to generate the image feature descriptor. Hear we computed color histogram feature (CHF) and bit pattern histogram feature (BHF), to measure the similarity between a query image and database image. The CHF and BHF are computed from the VQ-indexed color quantizer and VQ-indexed bitmap image, respectively. The distance computed from formula, the proposed indexing method outperforms the former BTC based image indexing and the other existing image retrieval schemes with natural and textural data sets. Thus, the proposed EDBTC is not only examined with good capability for image compression but also offers an effective way to index images for the content based image retrieval system.