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Fuzzy Mathematical Morphology approach in Image Processing

Morphological operators transform the original image
into another image through the interaction with the other image of
certain shape and size which is known as the structure element.
Mathematical morphology provides a systematic approach to analyze
the geometric characteristics of signals or images, and has been
applied widely too many applications such as edge detection,
objection segmentation, noise suppression and so on. Fuzzy
Mathematical Morphology aims to extend the binary morphological
operators to grey-level images. In order to define the basic
morphological operations such as fuzzy erosion, dilation, opening
and closing, a general method based upon fuzzy implication and
inclusion grade operators is introduced. The fuzzy morphological
operations extend the ordinary morphological operations by using
fuzzy sets where for fuzzy sets, the union operation is replaced by a
maximum operation, and the intersection operation is replaced by a
minimum operation.
In this work, it consists of two articles. In the first one, fuzzy set
theory, fuzzy Mathematical morphology which is based on fuzzy
logic and fuzzy set theory; fuzzy Mathematical operations and their
properties will be studied in details. As a second part, the application
of fuzziness in Mathematical morphology in practical work such as
image processing will be discussed with the illustration problems.

Binary Morphological, Fuzzy sets, Grayscalemorphology, Image processing, Mathematical morphology.