Abstract
This paper proposes an image edge detection method based on multi-directional, multi-scale Top-hat operators, and applies the method to the edge detection of OSAHS (Obstructive Sleep Apnea Hypopnea Syndrome) early pathological images. Firstly, construct multi-directional, multi-scale Top-hat operators, and they are used to detect the edge of image. Then the ideal image edge is obtained by combining the edges of the image detected by each operator according to a certain weight, so that we can calculate the actual area of the oral cavity accurately, and then achieve electronic medical diagnosis. The simulation results show that the operator proposed in this paper can filter out the noise better, preserve image detail more completely, so that the edge information of the image is more accurate and complete. Compared with conventional edge operator, it is more effective for image edge detection.
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