An Investigation Of Soft Morphological Edge-detection Algorithm Based On Fuzzy Theory

Edge is one of the basic characters of an image. Edge detection has been widely used in image processing, image analysis and computer vision, and it is the basis of them. So, Edge detection is always the hot and focus in the research field of digital image processing. There have been many algorithms proposed for the edge detection of images. But the existing theories and algorithms for edge detection still have some drawbacks and can not detect edges satisfactorily in some cases. And the problem of noise makes it available to further comprehension and analysis of the image.The fuzziness of the image makes it difficult to describe in a mathematical way, Due to ignorance of information loss in imaging process, it is difficult to describe premise knowledge accurately and mathematically. Moreover, because of unknown reasons caused by imaging process, there are likelihood and uncertainty between target and background. Fuzzy information processing technique developed from fuzzy set theory, have advantage to process uncertainty event and describe uncertainty knowledge. Mathematical morphology founded on set theory is a new method applied in the field of image processing and pattern recognition. Its prime principle is using a certain structuring element to measure and extract the corresponding form in an image so that we can analyze and recognize the image.Above all in this paper the basic theory of mathematical morphology is discussed, its application in image processing is analyzed and introduced as well. This paper makes an improved soft morphological edge-detection method based on fuzzy theory. This essay mainly including four aspects, which as follows:(1) Partition the image with a new method based on fuzzy degree.(2) Strengthen image in the fuzzy area by the improved rapid enhancement algorithm.(3) Design combination edge detection operator using soft- morphological properties;(4) Detect based on the fuzzy theory and soft-morphological.It is proved that the results applying the edge detection method based on fuzzy reasoning are better than those applying the traditional edge detection methods, it indicates that the method improved in this paper is more effective to detect edges than the traditional methods.