A convenient and robust edge detection method based on ant colony optimization

2015 ◽  
Vol 353 ◽  
pp. 147-157 ◽  
Author(s):  
Xiaochen Liu ◽  
Suping Fang
Keyword(s):  
Edge Detection ◽  
Ant Colony Optimization ◽  
Detection Method ◽  
Ant Colony ◽  
Edge Detection Method

scholarly journals An Image Edge Detection Method Based on Improved Ant Colony Algorithm

2011 ◽  
Vol 1 ◽  
pp. 236-240
Author(s):  
Xi Yun Wang ◽  
Pan Feng Huang ◽  
Ying Pings Fan
Keyword(s):  
Edge Detection ◽  
Ant Colony Algorithm ◽  
Detection Method ◽  
Ant Colony ◽  
Improved Method ◽  
Image Edge Detection ◽  
Image Edge ◽  
Edge Detection Method ◽  
Background Image ◽  
Improved Ant Colony Algorithm

This paper raises an improved ant colony algorithm, for the detection of weak edge of complex background image, considering edge positioning accuracy, edge pixels, edge continuity and interference edges. This algorithm is improved in two aspects: first, we improved the expression of pheromone; second, we improved the calculation of Heuristic information. Compared with traditional Canny detector indicates, the improved method is proved to be accurate in edge detection, good continuity and less interference by experiment.

scholarly journals Adaptive Ant Colony Optimization on Mango Classification Using K-Nearest Neighbor and Support Vector Machine

2017 ◽  
Vol 3 (2) ◽  
pp. 75 ◽  
Author(s):  
Febri Liantoni ◽  
Luky Agus Hermanto
Keyword(s):  
Support Vector Machine ◽  
Edge Detection ◽  
Ant Colony Optimization ◽  
Nearest Neighbor ◽  
Optimization Method ◽  
Ant Colony ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Edge Detection Method ◽  
Mango Leaves

Abstract— Leaves recognition can use an image edge detection method. In this research, the classification of mango gadung and manalagi will be performed. In the preprocess stage edge detection method using adaptive ant colony optimization method. The use of adaptive ant colony optimization method aims to optimize the process of edge detection of a mango leaves the bone image. The application of ant colony optimization method on mango leaves classification has successfully optimized the result of edge detection of a mango leaves the bone structure. Results showed edge detection using adaptive ant colony optimization method better than Roberts and Sobel method. The result an experiment of mango leaves classification with k-nearest neighbor method get accuracy value equal to 66,25%, whereas with the method of support vector machine obtained accuracy value equal to 68,75%.Keywords— Edge Detection, Ant Colony Optimization, Classification, K-Nearest Neighbor, Support Vector Machine

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