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http://dx.doi.org/10.20465/KIOTS.2022.8.1.059

Edge Detection using Cost Minimization Method  

Lee, Dong-Woo (Department of Computer Information, Woosong University)
Lee, Seong-Hoon (Division of Computer Engineering, Baekseok University)
Publication Information
Journal of Internet of Things and Convergence / v.8, no.1, 2022 , pp. 59-64 More about this Journal
Abstract
Existing edge discovery techniques only found edges of defined shapes based on precise definitions of edges. Therefore, there are many limitations in finding edges for images of complex and diverse shapes that exist in the real world. A method for solving these problems and discovering various types of edges is a cost minimization method. In this method, the cost function and cost factor are defined and used. This cost function calculates the cost of the candidate edge model generated according to the candidate edge generation strategy. If a satisfactory result is obtained, the corresponding candidate edge model becomes the edge for the image. In this study, a new candidate edge generation strategy was proposed to discover edges for images of more diverse shapes in order to improve the disadvantage of only finding edges of a defined shape, which is a problem of the cost minimization method. In addition, the contents of improvement were confirmed through a simple simulation that reflected these points.
Keywords
Edges; Cost factor; Cost function; Candidate edge; IoT;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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