Heterogeneous Face Detection

Abstract

Face detection is the process of determining the location of human faces in an image. Like human visual system, a face detection system should also be capable of achieving the detection task irrespective of illumination, absence of texture, orientation and camera distance. Detecting faces in heterogeneous, infrared and thermal images is a challenging job due to variation in texture, orientation, lighting condition, intensity etc. Many researchers have worked and proposed various methods for visible faces in the domain of face detection. However, face detection with the existing algorithm in heterogeneous face images is found quite difficult one. This paper attempts to improve the accuracy of an existing face detection algorithm which was basically designed for detecting visible faces, can now be used to detect heterogeneous faces by applying various image enhancement techniques before face detection. The proposed improved algorithm is suitable for heterogeneous face images which include thermal images, infrared images in the crowd. Attempts for the same have been tested on test image dataset. The experimental results are found to be encouraging.