Study on Wavelet Transformation-based Low Illumination & High Dirt Face Detection Algorithm
The paper1, above all, establishes a face database conforming to environmental features of low illumination and high dirt. Wavelet transformation is utilized in recognition algorithm so as to establish a weight-based cascade classifier by Harr features extracted from the picture. Law 6 serves to adjust weight between levels of cascade classifier. Pictures of actual coal miners are used as samples for training in the paper, to establish an initial classifier. The method is applied to face and eye recognition to obtain xml-based documents of classification features for face and eye recognition with good experimental effects. It has a high face detection rate. Besides, prototype system design based on face and eye recognition of video flow and picture is accomplished.
Face Recognition Wavelet Transformation Cascade Classifier Eye Recognition
Shubao Xing Huifeng Xue Gang Li
Northwestern Polytechnical University Science andTechnology University .Xian Shaanxi, China Northwestern Polytechnical University doctor in control science speciality Xian Shaanxi, china Northwestern Polytechnical University doctor in control science speciality Xian Shaanxi, china
国际会议
西安
英文
534-537
2011-05-13（万方平台首次上网日期，不代表论文的发表时间）