Object Segmentation Using Mean Removed Images

• Main Authors: Po-hsuan Chiu, 邱舶軒
• Other Authors: Yi-ching Liaw
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/7jwmbs

碩士 === 南華大學 === 資訊管理學研究所 === 95 === 　　In this thesis, we present a novel video object segmentation approach. The proposed approach extracts objects from a frame in a video stream using the difference information between the mean-removed versions of the current and referenced frames. Due to the mean-removed version of a frame reduces the influence of light variation on the frame and reserves the texture information of the frame, the proposed approach can effectively segment objects for video sequences and remove shadow pixels. Experimental results show that the proposed approach has the least computation time among object segmentation approaches with shadow removal capability. Compared with the available approaches, our approach reduces the computation time by 25% to 86% with better segmentation accuracy.