KFUPM ePrints

Content-based Image Retrieval using Multiple Shape Descriptors

Sarfraz, M. and Ridha, A. (2007) Content-based Image Retrieval using Multiple Shape Descriptors. Computer Systems and Applications, 2007. AICCSA '07. IEEE/ACS International conference, 1.

[img]Microsoft Word


In this paper we investigate content-based image retrieval using various shape descriptors. The descriptors include 11 moment invariants, area ratios (3-concentric ring based and 8-sector based) and simple shape descriptors (eccentricity, compactness, convexity, rectangularity, and solidity). The similarity measures used are Euclidean distance and Cosine correlation coefficient. For testing, 220 binary images from SQUID categorized into 12 image groups are used. Simple Shape Descriptors with Euclidean distance achieve the best average precision (0.593). Combining simple shape descriptors and area ratios, also using Euclidean distance as similarity measure, results in 3.29% improvement.

Item Type:Article
Date:May 2007
Date Type:Publication
Divisions:College Of Computer Sciences and Engineering > Information and Computer Science Dept
Creators:Sarfraz, M. and Ridha, A.
ID Code:14002
Deposited By:KFUPM ePrints Admin
Deposited On:24 Jun 2008 16:18
Last Modified:12 Apr 2011 13:14

Repository Staff Only: item control page