Face Recognition Using Block-based DCT and Weighted Generalized KFD

摘要：

An improved feature extraction for face recog nition is presented in this paper. In the proposed tech nique, the input face image is divided into blocks and two dimensional Discrete Cosine Transform (DCT) approach is applied to each block. Then the low frequencies of all two dimensional DCT coefficients from each block are extracted and combined to form a feature vector. Thereafter, weighted generalized kernel Fisher discriminant is performed on these vectors. Experimental results on the ORL face database demonstrate the effectiveness of the proposed method.

关键词： Face recognition Block-based discrete cosine transform Weighted generalized Kernel Fisher discriminant

作者: Jin Zou Feng Sun

作者单位: College of Mathematics and Information Science Leshan Normal University Leshan, China

会议类型: 国际会议

会议名称: 2010 4th International Conference on Intelligent Information Techonlogy Application(第四届智能信息技术应用国际学术研讨会 IITA 2010)

会议地点: 秦皇岛

会议语种:英文

页码: 483-486

在线出版日期: 2010-11-05（万方平台首次上网日期，不代表论文的发表时间）