中南民族大学学报（自然科学版）Issue(3)：100-104,5.
基于混沌粒子群优化算法的电力线检测
Detection of Power Lines Based on Chaotic Particle Swarm Optimization
摘要
Abstract
A line detection algorithm based on Chaotic Particle Swarm Optimization ( CPSO ) has been proposed and applied to the detection of power lines .First, the candidates for edge points are detected by Sobel operator .Then, a number of pairs of points are selected from the candidates for edge points as the initial particles .Each particle represents a line, and its fitness value is the number of candidate edge points collinear the line .In the iterative process , the worst particle is replaced with a new chaotic particle .Finally, the particle with the highest fitness is chose to be the line to be detected.The algorithm is applied to the power line detection , and the experimental results verify its effectiveness . Comparing with other algorithms such as Hough transform , the algorithm proposed in this paper can effectively reduce the problem of double counting and improve the accuracy and efficiency .关键词
粒子群优化算法/适应度/检测/Hough变换/电力线Key words
particle swarm optimization/fitness/detection/Hough transform/power line分类
信息技术与安全科学引用本文复制引用
徐胜舟,胡怀飞..基于混沌粒子群优化算法的电力线检测[J].中南民族大学学报（自然科学版）,2014,(3):100-104,5.基金项目
国家自然科学基金资助项目（61302192）；中南民族大学自然科学基金资助项目 （）
