FACE RECOGNITION METHOD USING DATA PROCESSING TECHNOLOGIES BASED ON HYBRID APPROACH AND RADIAL BASIS FUNCTION NEURAL NETWORKS

摘要

PURPOSE: An image data pre-processing method of a hybrid method and a face recognition method using RBFNNs(Radial Basis Function Neural Networks) are provided to improve recognition speed and recognition rates by identifying a face based on RBFNNs. CONSTITUTION: Face image data of a subject is obtained by using a CCD(Charge Coupled Device) camera(S100). An image correction process, an image area detection process, an image shape extraction process, and a characteristic extraction process are executed for the face image data(S200). The face is recognized from the face image data by using RBFNNs(S300). An image shape extraction process extracts a shape and detects a face line from a face area by using an ASM(Active Shape Model). A characteristic for the face line is set by using pixel value distribution. [Reference numerals] (AA) Start; (BB) End; (S100) Step of obtaining the face image data of a subject using a CCD camera; (S200) Pre-treatment step of executing the processes of correcting an image about the obtained face image data, detecting a face area, extracting a face contour, and extracting characteristics; (S300) Step of recognizing a face from the pre-treated image data using Radial Basis Function Neural Networks(hereinafter referred to as 'RBFNs');