A Comparison of Face Detection Algorithms in Visible and Thermal Spectrums
نویسندگان
چکیده
Face Detection is the first step of facial recognition algorithms and has been widely researched in the visible spectrum. Current research has shown that thermal facial recognition is as accurate as the visible spectrum recognition algorithms. This paper presents three face detection algorithms in both long-wavelength infrared (LWIR) images and visible spectrum images. The paper compares the ViolaJones algorithm, Gabor feature extraction and classification using support vector machines, and a Projection Profile Analysis algorithm. The Gabor feature extraction method can detect faces in both spectrums with separate training, but the algorithm is extremely slow. The Project Profile Analysis method can find faces in LWIR images, but is not applicable to visible spectrum images. Our experimental results show that the Viola-Jones algorithm is the most reliable and efficient solution for the implementation of a real-time face detection system using either visible or thermal spectrum images. Index Terms – Face Detection, Object Detection, Thermal Imaging, Image Processing
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