Digital Color Image Processing Using Intuitionistic Fuzzy Hypergraphs

Hypergraphs are considered a useful mathematical tool for digital image processing and analysis since they can represent digital images as complex relationships between pixels or block of pixels. The notion of hypergraphs has been extended in fuzzy theory leading to the concept of fuzzy hypergraphs, then in intuitionistic fuzzy theory conducting to the concept of intuitionistic fuzzy hypergraphs or IFHG. The latter is very suitable to model digital images with uncertain or imprecise knowledge. This paper deals with color image denoising, segmentation, and edge detection in a color image initially represented in RGB space using intuitionistic fuzzy hypergraphs. First, the RGB image is transformed to HLS space resulting in three separated components. Then each component is intuitionistically fuzzified based on entropy measure from which an intuitionistic fuzzy hypergraph is generated automatically. The generated hypergraphs will be used for denoising, segmentation, and edge detection.