Image Edge Tracking via Ant Colony Optimization

被引:0
作者
Li, Ruowei [1 ]
Wu, Hongkun [1 ]
Liu, Shilong [1 ]
Rahman, M. A. [1 ]
Liu, Sanchi [1 ]
Kwok, Ngai Ming [1 ]
机构
[1] Univ New South Wales, Sch Mech & Mfg Engn, Kensington, NSW 2031, Australia
来源
NINTH INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2017) | 2018年 / 10615卷
关键词
Edge Tracking; Edge Detection; Ant Colony Optimization;
D O I
10.1117/12.2303469
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
A good edge plot should use continuous thin lines to describe the complete contour of the captured object. However, the detection of weak edges is a challenging task because of the associated low pixel intensities. Ant Colony Optimization (ACO) has been employed by many researchers to address this problem. The algorithm is a meta-heuristic method developed by mimicking the natural behaviour of ants. It uses iterative searches to find the optimal solution that cannot be found via traditional optimization approaches. In this work, ACO is employed to track and repair broken edges obtained via conventional Sobel edge detector to produced a result with more connected edges.
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页数:8
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