In the proposed eyeglasses detection algorithm, block processing, region growing, and priori knowledge (i.e., low mean and variance within glasses areas, the shapes and locations of eyeglasses) are employed. The eyeglasses detection algorithm should produce either a binary mask if eyeglasses present, or an empty set if no eyeglasses at all. Of course, the searching region of a pair of eyeglasses is within the detected face area. In thermal face detection, a projection profile analysis algorithm is proposed, where region growing and morphology operations are used to segment the body of a subject then the derivatives of two projections (horizontal and vertical) are calculated and analyzed to locate a minimal rectangle of containing the face area. One possible solution is to detect eyeglasses and to exclude the eyeglasses areas before face matching. Infrared light cannot go through glasses and thus glasses will appear as dark areas in a thermal image. Face detection and eyeglasses detection are necessary steps prior to face recognition using thermal images. Thermal face recognition becomes an active research direction in human identification because it does not rely on illumination condition. To reinforce the accuracy of face detection, we further identify mouth and eye regions to establish the presence/absence of face in a particular region of interest.įace detection and eyeglasses detection for thermal face recognition
FACE DETECTION VB6 SKIN
The algorithm uses conjunction of skin color histogram, morphological processing and geometrical analysis for detecting human faces.
This paper proposes a robust algorithm for face detection in still color images that works well even in a crowded environment. Human face detection plays a vital role in many applications like video surveillance, managing a face image database, human computer interface among others. Raviteja, Thaluru Karanam, Srikrishna Yeduguru, Dinesh Reddy V.
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