8 Face Coding and Recognition using Line Edge Map

H Shukla, Ravi Verma, H Shukla, Ravi Verma
2015 unpublished
Much research in human face recognition involves front-parallel face images, constrained rotations in and out of the plane, and operates under strict imaging conditions such as controlled illumination and limited facial expressions. The automatic recognition of human faces presents a significant challenge to the pattern recognition research community. Typically, human faces are very similar in structure with minor differences from person to person. They are actually within one class of human
more » ... e. Furthermore, lighting condition changes, facial expressions, and pose variations further complicate the face recognition task as one of the difficult problems in pattern analysis. This paper proposed a novel concept; "face coding and recognition using Line Edge Map". A compact face feature, Line Edge Map (LEM), is generated for face coding and recognition. The system performances are compared with the eigenface method, one of the best face recognition techniques, and reported experimental results of other methods. A face pre-filtering technique is proposed to speed up the searching process. It is a very encouraging finding that the proposed face recognition technique has performed superior to the eigenface method in most of the comparison experiments. This research demonstrates that LEM together with the proposed generic line segment Hausdorff distance measure provide a new way for face coding and recognition.
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