eprintid: 1559
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/15/59
datestamp: 2023-11-09 15:49:43
lastmod: 2023-11-09 15:49:43
status_changed: 2023-11-09 15:40:52
type: conference_item
metadata_visibility: show
creators_name: Malik, F.-E.
creators_name: Baharudin, B.B.
creators_name: Ullah, K.
title: Efficient image retrieval based on quantized histogram texture features in DCT domain
ispublished: pub
keywords: Compressed domain; Content-Based Image Retrieval; Critical information; DCT; DCT domain; Discrete cosine transformation; Local compression; Perceptual information; Pixel domain; Quantized histogram; Retrieval performance; Retrieval systems; Statistical texture features; Texture features, Content based retrieval; Graphic methods; Image coding; Information retrieval; Information technology; Textures, Image texture
note: cited By 4; Conference of 2011 9th International Conference on Frontiers of Information Technology, FIT 2011 ; Conference Date: 19 December 2011 Through 21 December 2011; Conference Code:88534
abstract: Huge number of images is available on the internet. Efficient and effective retrieval system is needed to retrieve these images by the contents or features of the images like color, texture and shape. This system is called content based image retrieval (CBIR). Conventionally features are extracted from images in pixel domain. But at present almost all images are represented in compressed form using DCT (Discrete Cosine Transformation) blocks transformation. Some critical information is removed in compression and only perceptual information is left which has significant attraction for information retrieval in compressed domain. In this paper we study the problem that how to retrieve perceptual information in compressed domain JPEG such that to improve image retrieval. Our approach is based on quantized histogram statistical texture features in DCT blocks. We show that to get best image retrieval performance by extracting the statistical texture features of quantized histogram in DCT blocks using JPEG compressed format images. Experiments on the Corel animal database using the proposed approach, give results which show that the statistical texture features of histogram are robust in retrieval of images. This shows that texture features in local compression is a significant step for effective image retrieval. © 2011 IEEE.
date: 2011
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857180934&doi=10.1109%2fFIT.2011.24&partnerID=40&md5=2d13f7a9400a693c6b9f9db4267b12f4
id_number: 10.1109/FIT.2011.24
full_text_status: none
publication: Proceedings - 2011 9th International Conference on Frontiers of Information Technology, FIT 2011
place_of_pub: Islamabad
pagerange: 89-94
refereed: TRUE
isbn: 9780769546254
citation:   Malik, F.-E. and Baharudin, B.B. and Ullah, K.  (2011) Efficient image retrieval based on quantized histogram texture features in DCT domain.  In: UNSPECIFIED.