Face Detection using Color based Segmentation and Edge Detection

Abstract

The increasing use of computer vision in security in place of humans led many to research the problem of face detection in images. The problem is not a petty one as the classification of a human face proves to challenging. Despite the many variations of a human face, features can still be found, given a certain context, which will uniquely identify a face. Early face-detection algorithms focused on the detection of frontal human faces, whereas this paper attempt to solve the more general and difficult problem of multi-view face detection. Face detection involves many research challenges such as scale, rotation, and pose and illumination variation. The techniques used for face detection have been researched for years and much progress has been suggested in literature. This paper proposes a new technique for detecting faces in color images using color model and edge detection. Face detection is used in as a part of a facial recognition system. It is also used in human computer interface, image database management and video surveillance. The results of this technique show that the proposed algorithm is good enough to detect the human face taken through video with accuracy. This paper is achieving high detection speed, high detection accuracy and reduces the false detecting rate.

Analysis of skin color models for face detection

“…The YCbCr color model represents image in three components; one is luminous component and remaining two are chrominance components [4]. The chrominance components are not depends on luminance component.…”

Faces Detection using Skin Color, Region-Props, Bounding-Box and Neural Networks System

“…The concepts of facial geometry are used to locate the mouth, eyes and nose positions (Kalbkhani et al, 2013). Some articles presented techniques for detecting faces in color images using various color models and edge detection (Tiwari and Ahmed, 2013;Goswami et al, 2013;Perumal and Perumal, 2013). A face detection method presents controlled weights on the three components of HSV color model these components are Hue (H), Saturation (S) and Intensity value (V) as explained in (Rewar and Lenka, 2013).…”