Facial Mole Detection: An Approach towards Face Identification

Abstract Face is the most significant biometric as it reveals a person's identity more accurately. Soft biometric traits like facial marks have played a crucial role in identifying a human face. The paper presents an automatic prominent mole detection and validation technique which can reduce the adverse effect of illumination in face recognition. Normalized cross-correlation with LoG filter is used to detect the facial mole candidates. A contributory threshold based step is introduced in this paper to improve the accuracy of the mole detector. The mole detection rate is 91.67% using our own developed “DeitY-TU” face database and 90.58% using FEI face database.

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