Application Of Edge Detection Based On Self - Image And Its Morphology In Shadow Image

Image edge detection is a very important part in image processing. It is widely used in the field of computer vision, texture analysis and feature extraction. There are a lot of methods in the field of edge detection, but in view of the analysis of the noise and the environment of the image, the performance of each method is different. It is an important research direction in the field of image edge detection to extract the original image with high accuracy and good anti noise performance.The traditional edge detection operator can detect the edge details of the image without noise. However, in the case of noise, the detection results will be greatly affected. The mathematical morphology detection technology provides a good solution for the edge detection, which can effectively filter out the noise effect by the morphological operator and structural elements. However, in addition to the noise effect, the external illumination environment will have a greater impact on the detection results. Therefore, this paper in the light of the light shaded conditions, to study to light according to the shadow of self quotient image algorithm based on non noise and noise problem of edge detection, the edge detection based on self quotient image and the traditional edge detection to solve the noise problem of; in self quotient image and morphological edge detection operator to solve the noise problem of edge detection.The main contents of this article are as follows:(1) The research background and the significance of the selected topic are introduced in this paper, which is based on the actual situation of the image features. The current research status of the existing edge detection methods at home and abroad is summarized, and the problems in the application of edge detection in the light shadow environment are proposed.(2) The theoretical basis of the self-quotient map is described, and the advantages of the derivation of the self-quotient map and the shadow image are introduced.(3) In the light of the shadow environment, the edge detection of the image without noise, the improved algorithm, the initial introduction of the advantages of image enhancement algorithm, combined with the traditional edge detection operator for edge detection. The simulation results show that the new algorithm detects the contour information more and the edge details more clearly in the light and shadow environment and no noise. However, in the case of noise, the test results are not the best.(4) The edge detection problem in the real noise background is studied, and the algorithm based on the self quotient graph and morphological edge detection is proposed. Introduced through dilation, erosion, opening and closed operation characteristics to construct new anti noise performance of the operator, and the self quotient image algorithm to shadow characteristics and image enhancement characteristics by combining light shadow and noise in the image. Experimental results show that the new algorithm can not effectively remove the noise, the noise can be very good here, and in the shadow of the environment, can be very good to detect the details of the information.(5) In the front several chapters of the proposed algorithm based on the proposed realization based on Matlab GUI shadow image edge detection software, introduces in detail the GUI design steps, camera settings information and the whole frame of the building.