A Hierarchical Fuzzy Based Approach for Face Detection
In this paper, we propose an algorithm for face detection in 2D intensity images. The method has two steps: extracting face candidates and filtering out the false positives. In the first stage we provide a face model by combining intensity and edginess information of face image. The extracted features are fuzzified to overcome the problem of variations in imaging system. We provide a fuzzy model for the most representative parts of face (lip, eyes and forehead). The applying first part on input image results a number of locations candidate as face. In the second part we use a Neural network to filter out false positives from the list of candidates for face. We train this part using face and non-face images. The result of experiments on intensity face images in complex scene is very promising.
Fuzzy face detection Edginess feature eztraction Neural network
ALIREZA AHMADYFARD BARDIA YOUSEFI SEYED MOSTAFA MIRHASSANI
Department of Electrical Engineering Shahrood University of Technology Shahrood, Iran Department of Electronic Engineering SRBIAU,Science & research BIAU Tehran, Iran
国际会议
上海
英文
2327-2330
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）