An intelligent web service for classifying digital imagery by using rough sets

Abstract

Integrating recent developments in service-orientated computing, Web technologies and computational intelligence has facilitated the development of applications for solving complex problems in several fields of scientific and technological research. Rough sets theory provides a solid theoretical background within the computational intelligence (CI) field for the qualitative reasoning required for analysing datasets loaded with uncertainties due to the vagueness and lack of precision associated with them. This paper describes the development of an intelligent Web service to process digital imagery, demonstrating the benefits of rough sets theory in dealing with the flexible supervised classification of the pixels associated with them.

Keywords

• rough sets
• indiscernibility
• lower approximation
• upper approximation
• decision system
• Web service
• digital image