The thesis illustrates the development of DSP-based systems-¡§DSP Based Face Characteristic Extraction and Identity Recognition System¡¨.The principal system consists of three major subsystems and two kinds of structure of recognition algorithms.Three major subsystems are Image Acquisition System.Image Preprocessing System,and face characteristic extraction individually.Two kinds of structure are Competitive Neural Network and Gaussian mixture model respectively In actual proving,we adopt colored half-length face image alone only face image,and simulate on PC.In order to acquire the characteristic parameter with the different parts to the people faces , and then achieve the purpose that the identity discerns.Finally implant it to DSP .Shown by the experimental result,this system can really reach the anticipative goal,and gain good recognition and efficiency.

The thesis illustrates the development of DSP-based¡§Real-Time Human Face Recognition System¡¨.The principal system consists of three major subsystems.There are Image Acquisition System¡AImage Preprocessing System and human face characteristic extraction . For experiment,we adopted colored face image with complex background and simulate on PC.We found the characteristic points and characteristic vectors from the face image which is searched from Gene algorithm.Then,we use the recognition system to recognize the face image.Finally we implant it to DSP. Shown by the experimental result,this system has good recognition and efficiency.