Linear Feature Enhancement Using Directional Filtering and Neural System
Faculty of Computing, Health and Science
School of Computer and Information Science
Recognizing linear information in some selective directions is required sometimes in image processing. Directional filters can be made in some specific directions so that the interested linear features in these directions are enhanced. Traditionally the results of directional filtering in these directions are presented in separate images, which is inefficient in revealing the relationships between linear features in these directions. In this paper, we propose a new approach that uses a neural system to coordinate all the results from directional filtering in several directions to produce an integrated image that presents the enhanced linear features in one or more of these directions. The synthetic and real examples presented in this paper prove that the combination of neural system and directional filtering is useful for linear feature enhancement.