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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.