Abstract
This paper discusses a fuzzy-directed graph-based theoretical technique for image analysis. Due to the property that, in a fuzzy graph, the membership grade of the edges must be less than or equal to the minimum of the membership grades of the end vertices, they do not straightaway represent an image. First, a novel method to overcome this barrier is proposed by directly transforming an image as a collection of fuzzy directed graphs using a fuzzy graph-based matrix swap algorithm. Second, the fuzzy graph terminologies for representing images are described through main definitions and theorems. Finally, the application of the algorithm is demonstrated with the help of a fuzzy inference system under two different scenarios of image classification.
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