THE METHOD OF EDGE DETECTION BASED ON NEURAL NETWORK AND THE MEASURE OF IMPORTANCE OF POINTS
基于神经网络和点的重要性度量的边缘提取方法

Based on the scale and the state of intensity distribution in some neighborhoods of edge points, this paper proposes a measure vector of importance of point that consists of 4 components and corresponds to every point. For considering the background of application, this paper first trains a BP neural network using some samples that have classified by manual work, and then extracts more important edge points in a new image using the trained neural network. Because the image needs not be smoothed by some function in this algorithm, the edge deflection will not happen as usual, the location of gotten edge is in the accurate position. The effectiveness of this algorithm has been testified by some experiments.