n South African Computer Journal - Image classification and retrieval algorithm based on rough set theory : research article

Volume 2003, Issue 30
  • ISSN : 1015-7999
  • E-ISSN: 2313-7835



This paper presents an efficient algorithm to classify and retrieve images from large databases in the context of rough set theory. Color and texture are two well-known low-level perceptible features to describe an image's contents used in this paper. The features are extracted, normalized and then the rough set dependency rules are generated directly from the real valued attribute vector. Then the rough set reduction technique is applied to find all reducts of the data which contains the minimal subset of attributes that are associated with a class label for classification. We test three different popular distance measures in this work and find that quadratic distance measures provide the most accurate and perceptually relevant retrievals. The retrieval performance is measured using recall-precision measure, as is standard in all retrieval systems.

Loading full text...

Full text loading...


Article metrics loading...


This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error