Research On Image Edge Detection And Application Of Soft Morphology

Edge detection is the foundation of feature description, image segmentation, image enhancement, pattern recognition and image compression and so on. Also edge detection is a hot topic in digital image processing.Mathematical morphology founded on set theory is applied in the field of image processing and pattern recognition. Its main principle is to use a certain structuring element to measure and extract the conesponding form in an image so that the image can be analyzed and recognized. Soft morphology is an important subclass of development of mathematical morphology. This makes more tolerant and robust to noise. In this paper, the traditional theory and new method are introduced at first, then many different algorithms are simulated.Then the basic theories of morphology and soft morphological are introduced systemically. Some researches are made based on the soft morphology theories as the follows.This paper applies the PSO to the soft morphology to select soft morphology of the best image edge detection method aimed at a single size structure element. The method is approved to be simple, suitable and effective. But when a large number of noises are included in an original image, the restraining noises capability of soft morphology with single structure element is worse than that with multi-scale structure elements. So the applications of soft mathematical morphology with multi-scale structure elements are researched in the image edge detection. It was proved by large numbers of experiments that the algorithm proposed by the paper is better to restrain noises and extract useful image edge information than traditional methods under the interrupt of a great many of noises.Finally, the extensive applications of soft morphology in practice are summarized.