Image Edge Detection Algorithm Is A Comparative Study

In image processing, as a basic characteristic, the edge of theimage, which is widely used in the recognition, segmentation,intensification and compress of the image, is often applied tohigh-level domain.There are many kinds of ways to detect the edge. Anyway, there aretwo main techniques: one is classic method based on the gray grade ofevery pixel; the other one is based on wavelet and its multi-scalecharacteristic. The first method, which is got the longest research,get the edge according to the variety of the pixel gray. The maintechniques are Robert, Laplace, Sobel, Canny and LOG algorithm. Thesecond method, which is based on wavelet transform, utilizes theLipschitz exponent characterization of the noise and singular signaland then achieve the goal of removing noise and distilling the realedge lines. In recent years, a new kind of detection method, which basedon the phase information of the pixel, is developed. We need hypothesizenothing about images in advance. The edge is easy to find in frequencydomain. It's a reliable method.In chapter one, we give an overview of the image edge. And inchapter two, some classic detection algorithms are introduced. Thecause of positional error is analyzed, and then discussed a moreprecision method in edge orientation. In chapter three, wavelet theoryis introduced. The detection methods based on sampling wavelettransform, which can extract maim edge of the image effectively, andnon-sampling wavelet transform, which can remain the optimum spatialinformation, are recommended respectively. In the last chapter of thisthesis, the algorithm based on phase information is introduced. Usingthe log Gabor wavelet, two-dimension filter is constructed, many kindsof edges are detected, including Mach Band, which indicates it is aoutstanding and bio-simulation method.May all the work in this paper is of some value to research and...