摘要
针对在弱光环境下的人体跟踪问题,本文提出一种带色素信息蚁群检测的弱光环境人体跟踪算法。通过利用蚁群优化算法检测监控帧图像里的物体边缘,并在初始帧图像里为聚集在边缘的蚁群身上标记色素信息,采用带色素的蚁群检测带信息素的蚁群并向其聚拢的性质来实现对处于弱光环境下的运动人体进行跟踪的目的。实验数据分析及仿真结果表明,本文的人体跟踪算法对处于弱光环境下的运动人体具有跟踪实效性,对存在噪声的图像也具有一定的鲁棒性。
As to the human body tracking problem under the weak light environment, human body tracking algorithm of ant colony detection with pigment information is presented. The character of ant colony optimization algorithm was used to detect the monitoring initial frame image object edge, and in the initial frame image to gather on the edge of the ant colony body, pigment information is marked. By using pigments ant colony detected with pheromone ant colony and toward pheromone ant colony gather, the purpose of tracking for human movement at night is achieved. The experimental data analysis and simulation results show that the human tracking algorithms for human movement under the low light environment is effective, and also has certain robustness for an image with noise.
出处
《光电工程》
CAS
CSCD
北大核心
2013年第3期20-28,共9页
Opto-Electronic Engineering
关键词
蚁群优化算法
边缘检测
色素信息
ant colony optimization algorithm
edge detection
pigment information