Research On The Applications Of The Facial Feature Location And Template Matching Based Face Detection Algorithm

This dissertation is dedicated how to detect the facial feature of the frontal humanface on a static colorized image and consequently detect the human face. As a keytechnique in the field of computer vision, face detection and facial feature location hasmany potential important applications on a wide range of fields including videosurveillance, face recognition system and the human-computer interaction system of thenew generation. Many domestic and international academic discourses and researchreports on face detection and facial feature location are collected and analyzed in thedissertation, which carries through an in-depth research on how to establish the frontalhuman face detection system. In the dissertation a facial feature location and templatematching based algorithm on face detection is put forward after a careful research on theprevious researchers' achievements. We establish a facial feature location and templatematching based face detection system on PC and experiments are carried.This analyzed project is mainly divided into two parts. The first part is research andapplication on the algorithm of the human face detection. And the second part is thedesign and implementation of the facial feature location and template matching basedface detection system. Human face detecting is to locate the position and the size ofhuman face in the static image or the video sequence. The difficulty in detecting thehuman face is to decide the method of searching which is used to locate the human facein an image. This analyzed project put forward the combination between the mainlylocation of human face based on the characters and the precise location of human facebased on the template. The system provides the candidate face using face feature in therough search and confirm the results in the careful search based on the human facetemplate. The experiment shows that the algorithm can achieve certain effects and adaptto many environment. In the system's design and implementation part, some knowledgeof the digital image processing is imported due to the need of the facial feature locationand template matching based face detection. Considering the usability of the digitalimage processing, the system includes the module of digital image processing.This facial feature location and template matching based algorithm achieves certaineffects and precision in the face detection.