Research On Image Characteristic Extraction Algorithm Based On Edge And Corner

With the development of social science and technology, human society has entered into a brand-new digital era. As an important carrier of information, it is significant to do efficient research and expression with image. Image character can be used as the property of notes in the image, however, at the same time, this becomes a hot and difficult area in the digital image research. Correctly extracting image property is the research basis and key premise of image segmentation, image understanding, pattern recognition and computer vision. Within all of the image characteristics, image edge and corner are of greatest importance, because they can relatively depict the characteristics of the image thoroughly. Image edge can be defined as the discontinued area of partial character of image grayscale, textures and color, while corner is the most peculiar type of edge corner. It is the terminal of sharp edge and usually it can be defined as the corner where curvature is high enough or curvature that changes often enough as well. Image edge detection and corner detection are the crucial research content in the image character extract area and the basis of subsequent image processing.Firstly, this paper thoroughly compares the main classic edge detection algorithm and analyses the advantage and disadvantages in the traditional SUSAN corner algorithm. Through the comparison, it is found that there are lacks of noise filter system or the filter system is relatively weak and a lack in the methods to strength the fuzzy image character, and there are no any multi-scale methods to reduce the multi-response from image characteristics or incorrect image characteristics detection which is caused by noise interference neither. According to all weakness raised above, this paper provides a series of new solutions, the main content includes three aspects shown as below.1) The paper counters the situation of the bad effect of noise filter with a set algorithm composed of three improved filter algorithms (CS-LAMF,ASF-M,CS-GF) which reserve image details to deal with pepper noise, Gaussian noise and mixed noise respectively, meanwhile it can reduce the fuzziness of the image characteristics.2) It also introduces some related morphological theory in mathematics to strengthen the character property after wave filtering and propose a brand-new edge detection algorithm based on Canny which is also self-adaptive to noise type.3) It finally raises a new self-adaptive improved corner detection algorithm based on SUSAN which is combined the idea from Harris algorithm's design with using default template to match and eliminate fake corner, making SUSAN threshold self-adaptive and setting upper limit/low limit to the original corner response value.From the comparative lab data, we can find the new filter system can finely maintain details of the image property while improve the filter effects at the same time, the new edge detection algorithm has detected better results than traditional algorithm in the condition of multi type noises, the proposed corner detection algorithm also can provide better detection results while reserve a good real time performance as well.