关键词: 运动目标检测, 视频水印, 自适应人工蜂群, Powell 搜索, Logistic-正弦映射, Arnold 映射

Abstract: In order to solve the problem that the motion vector search is inefficient and the embedded
watermark information is single, this paper integrates adaptive artificial bee colony and Powell local search
to realize a moving object detection method based on independent component analysis. Adaptive search
parameters are used to adjust neighborhood search scope dynamically, that makes artificial bee colony
algorithm quickly converge to global optimal and achieve a more optimal solution. Then, all nectaries will
be clustered by K-mean to be dependence of clustering result on the initial center, and then clustering results
are divided into Powell local search, which accelerate the algorithm convergence speed. The motion
component optimization problem is designed by using the independent component, and the optimal solution
is solved by the improved method to extract the motion component in the video sequence. By using
Logistic-sinusoidal mapping for chaotic encryption, the Arnold map is scrambled on the encrypted
watermark image, and the final watermark information is embedded in B frame and P frame, and the real
integrity of the video data is enhanced while improving the video data attack. The simulation results show
that the hybrid watermark embedding algorithm has good performance in robustness and vulnerability.

Key words: moving target detection, video watermark, artificial bee colony, Powell search, Logistic-sine mapping, Arnold mapping