EXTRACTING FEATURES OF THE HUMAN FACE FROM RGB-D IMAGES TO PLAN FACIAL SURGERIES

Abstract

Biometric identification of the human face is a pervasive subject which deals with a wide range of disciplines such as image processing, computer vision, pattern recognition, artificial intelligence, and cognitive psychology. Extracting key face points for developing software and commercial devices of face surgery analysis is one of the most challenging fields in computer image and vision processing. Many studies have developed a variety of techniques to extract facial features from color and gray images. In recent years, using depth information has opened up new approaches to researchers in the field of image processing. Hence, in this study, a statistical method is proposed to extract key nose points from color-depth images (RGB-D) of the face front view. In this study, the Microsoft Kinect sensor is used to produce the face RGB-D images. To assess the capability of the proposed method, this algorithm is applied to 20 RGB-D face images from the database collected in the ICT lab of Sahand University of Technology and promising results are achieved for extracting key points of the face. The results of this study indicated that using the available information in two different color-depth bands could make key points of the face more easily accessible and bring better results and we can conclude that the proposed algorithm provided a promising outcome for extracting the positions of key points.