Image Edge Detection Algorithm

Edge is one of the basic characters of an image, which contains a great deal of useful information and offers people important parameters to describe and recognize objects in an image. Edge detection is one of the most fundamental operations in image processing, image analysis and computer vision. It is one of the basic methods for pattern recognition and image information extraction. The field of edge detection has been an active research area for several decades. There are probably more algorithms for edge detection in the literature than for any other single subject. Images obtained from real-world scenes are generally buried in noise. Both edges and noise may be obtained in an attempt to detect edges from an image with a large amount of noise. How to detect edges reliably and accurately in the presence of noise has remained an important issue in the field of edge detection.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 technology of artificial neural networks is a new branch of the field of artificial intelligence, which has been developing quickly in recent years and applied widely to areas of information processing, pattern recognition and intelligent control and system-modeling. The BP neural network is one of the most popular models of neural networks and has been widely used. The BP neural network has simple architecture and...