{"title":"Fuzzy Mathematical Morphology approach in Image Processing","authors":"Yee Yee Htun, Dr. Khaing Khaing Aye","country":null,"institution":"","volume":18,"journal":"International Journal of Computer and Information Engineering","pagesStart":1997,"pagesEnd":2004,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/1511","abstract":"Morphological operators transform the original image\r\ninto another image through the interaction with the other image of\r\ncertain shape and size which is known as the structure element.\r\nMathematical morphology provides a systematic approach to analyze\r\nthe geometric characteristics of signals or images, and has been\r\napplied widely too many applications such as edge detection,\r\nobjection segmentation, noise suppression and so on. Fuzzy\r\nMathematical Morphology aims to extend the binary morphological\r\noperators to grey-level images. In order to define the basic\r\nmorphological operations such as fuzzy erosion, dilation, opening\r\nand closing, a general method based upon fuzzy implication and\r\ninclusion grade operators is introduced. The fuzzy morphological\r\noperations extend the ordinary morphological operations by using\r\nfuzzy sets where for fuzzy sets, the union operation is replaced by a\r\nmaximum operation, and the intersection operation is replaced by a\r\nminimum operation.\r\nIn this work, it consists of two articles. In the first one, fuzzy set\r\ntheory, fuzzy Mathematical morphology which is based on fuzzy\r\nlogic and fuzzy set theory; fuzzy Mathematical operations and their\r\nproperties will be studied in details. As a second part, the application\r\nof fuzziness in Mathematical morphology in practical work such as\r\nimage processing will be discussed with the illustration problems.","references":null,"publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 18, 2008"}