Real-time Segmentation of Video with Stationary Background Based on Morphological Edge Processing

• Main Authors: I-Shan Huang, 黃奕善
• Other Authors: David W. Lin
• Format: Others
• Language: en_US
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/55500010545781263001

碩士 === 國立交通大學 === 電機學院碩士在職專班電子與光電組 === 95 === In the thesis, we consider the design and implementation of video segmentation on a personal computer. The system can be applied on video conference and videophone with stationary background. The basic idea of the system is a graph-based edge linking technique. At first, we adopt a two staged method for camera noise estimation and those thresholds are adjusted based on the estimated camera noise. To get the change detection mask, we consider six consecutive frames as time of observation to estimate the background and select a suitable threshold to estimate the foreground by two consecutive frames. Next, we use Canny edge detector to get the edge information of entire frame. We use the change detection mask and the moving object mask of previous frame to remove the edges of background. Then, we shrink the object mask to edge map. To refine the object mask, we use Dijkstra’s shortest path search algorithm to link the boundary of moving object and extract the object by the closed contour. Simulation results show that our method can give correct segmentation results. After optimization, the proposed segmentation system can get the moving object accurately and quickly. With a Intel Pentium M 1.733 GHz CPU and 1024-MB RAM, the system can achieve 20 QCIF frames per second and 4 CIF frames per second. We also propose a simple method and it can achieve 12 CIF frames per second.