A Smart Digital Surveillance System with Face Tracking and Recognition Capability

• Main Authors: Tai-Shiang Huang, 黃泰祥
• Other Authors: Sean-Gang Miaou
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/91528885445376793248

碩士 === 中原大學 === 電子工程研究所 === 92 === In order to substitute for the existing analog type surveillance systems having digital <a href="http://www.ntsearch.com/search.php?q=storage&v=56">storage</a> function, this paper presents a smart digital surveillance system with face tracking and recognition capability. If an invader is detected by the system, the system can promptly send out the alarm and SMS (Short Message Service), and store relevant image frames. The system can be divided into two sub-systems, i.e. face detection and tracking and face recognition. The human face detection and tracking sub-system identifies the possible face region using skin color information, achieving the preliminary positioning of the face, and control the P/T/Z (Pan-Tilt-Zoom) <a href="http://www.ntsearch.com/search.php?q=camera&v=56">camera</a> to track the object. After the preliminary face positioning we locate the face outline using an ellipse mask, and finally detect the eyes and the lip to confirm if the object of interest is indeed the human face. For the face recognition, we apply a two dimensional wavelet transform for the dimensionality reduction of face image. This method is able to overcome the drawback in traditional extraction of face features. In addition, we use the LDA (Linear Discriminant Analysis) to transform the features into a new space that has better separability. Finally, we employ the minimum Euclidean distance to determine the most likely person. The experimental results in face positioning part show that the successful rate is 98.4% in a simple background environment. For the face recognition part, the recognition rate for a <a href="http://www.ntsearch.com/search.php?q=single&v=56">single</a> image reaches 94%. Finally, the computation <a href="http://www.ntsearch.com/search.php?q=time&v=56">time</a> of the entire face recognition system is 0.26 seconds on the average, using a P4 2G <a href="http://www.ntsearch.com/search.php?q=personal&v=56">personal</a> <a href="http://www.ntsearch.com/search.php?q=computer&v=56">computer</a>.