Nowadays, face detection plays an important role in many application areas such as video surveillance, human computer interface, face recognition and face image database management etc. In face detection applications, face usually form an inconsequential region of images. Consequently, preliminary segmentation of images into regions that contain "non-face" objects and regions that may contain "face" candidates can greatly accelerate the process of human face detection. Color information based methods take a great attention, because colors have obvious character and robust visual cue for detection. This paper presents a new color thresholding method for detecting and tracking multiple faces in video sequence. The proposed method calculates the color centroids of image in RGB color space and segments the centroids region to get ideal binary image at first. Then analyze the facial features structure character of wait-face region to fix face region. The novel contribution of this paper is creating the color triangle from RGB color space and analyzing the character of centroids region for color segmenting. The experimental results show that the proposed method can achieve ideal thresholding result and it is much better than other color analysis based thresholding methods and can overcome the influence of background conditions, position, scale instance and orientation in images.

 Keywords: Face detection, Color image thresholding, Color centroids segmentation.

(P1150843440, 1.56 MB)

BibTex:

@ARTICLE{P1150843440,

AUTHOR = {Jun Zhang and Qieshi Zhang and Jinglu Hu},

TITLE = {RGB Color Centroids Segmentation (CCS) for Face Detection},

JOURNAL ={ICGST International Journal on Graphics, Vision and Image Processing, GVIP},

}

(P1150843440, 1.56 MB)