Title :
Content-based Image Retrieval using Multiple Shape Descriptors
Author :
Sarfraz, M. ; Ridha, A.
Author_Institution :
King Fahd Univ. of Pet. & Miner., Dhahran
Abstract :
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.
Keywords :
content-based retrieval; correlation methods; image retrieval; Euclidean distance; content-based image retrieval; cosine correlation coefficient; multiple shape descriptor; Computational efficiency; Computer science; Content based retrieval; Euclidean distance; Histograms; Image retrieval; Information retrieval; Minerals; Petroleum; Shape measurement;
Conference_Titel :
Computer Systems and Applications, 2007. AICCSA '07. IEEE/ACS International Conference on
Conference_Location :
Amman
Print_ISBN :
1-4244-1030-4
Electronic_ISBN :
1-4244-1031-2
DOI :
10.1109/AICCSA.2007.370714