Fast image moving object segmentation based on block texture for embedded system implementation
Shyue-Wen Yang, Ming‐Hwa Sheu, Wen‐Kai Tsai · 2012
In this paper, we present a new moving object detection approach based on block texture. It can dramatically reduce the memory size when constructing the background model in a dynamic scene. The proposed background model and detection algorithm are suitable for implementing on embedded system platform which always has resource limitation. From the experimental results, our detection quality achieves 78% similarity in average. The memory consumption can be reduced 47.92% when comparing with the existing algorithms. Finally, the operation performance can be demonstrated on embedded system platform with 10 frames per second.