Edge Detection Based On Catastrophe Theory

Edge detection is one of the most fundamental operations in image processing, image analysis and computer vision and offers people important parameters to describe and recognize objects in an image. 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. It is hard to propose a general method of edge detection applied to all cases. So, it has been the focus of current research work to find new methods for edge detection with specific application requirements or to make improvements to existing methods.The first time we apply Catastrophe Theory to research the characteristics of mutation of image, base on need of the problem, apply of cusp catastrophe theory to build edge model to detect edge and build catastrophe model to analyze the law of systemic state. Experimental results show that the method given by this paper can accuratly detect continue edge and have good real-time.