A Modified Ant Colony Based Approach to Digital Image Edge Detection
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
View: 528
This Paper With 7 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
این Paper در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
KBEI02_296
تاریخ نمایه سازی: 5 بهمن 1395
Abstract:
Ant Colony Optimization (ACO) is a nature inspired meta-heuristic algorithms, which can be applied to a wide range of optimization problems. In this paper we present a modified method for edge detection based on the Ant Colony Optimization. Because of disadvantages of traditional edge detection methods, ACO as a relatively new meta-heuristic approach has been used to solve the edge detection problem. The performance of proposed method is compared with traditional ant colony methods, also we have large number of experiments to find out the suitable threshold for proposed method. The experimental results clearly indicate how the ACO can extracts edges in efficient way, also we speed up the proposed method by modifying the effective parameters in speed of the problem and replacing them by optimized values. The results show that this method is faster and more efficient than other former Ant Colony-based edge detection methods
Keywords:
Authors
Aydin Ayanzadeh
Computer Science Department, Faculty of mathematical sciences, University of Tabriz, Tabriz, Iran
Hossein Pourghaemi
Computer Science Department, Faculty of mathematical sciences, University of Tabriz, Tabriz, Iran
Yousef seyfari
Computer Science Department, Faculty of mathematical sciences, University of Tabriz, Tabriz, Iran