Design And Realization Of The Face Detection Algorithm Based On The DSP

Face detection is one of the important researching aspects of human-machine, interaction based on the image processing, which means that find and locate all the human faces in the still images or video sequences in spite of the variation of the faces’location, size,orientation, posture and the illumination in the images. Besides, as a key technique in the human face information processing, face detection has the increasingly extensive application of identity recognition, content based retrieval, automatic monitoring, human-machine interaction and so on. At Present it has become the search hotspot in the field of pattern recognition and computer vision.The paper works out the system’s general Structure of hardware and software. Concerning the hardware, the hardware system platform composed by the DSP (Digital Signal Processors), TMS320DM6437, produced by the TI Corporation as the Processor-to construct an applied hardware system. On the other hand, the software integrate development environment of this system is CCS (Code Composer Studio)60003.3.DSP/BIOS which is the real time operation system (RTOS) can convenient to achieve real-time scheduling and real-time debugging.In the aspect of algorithmic design, this paper describes the basic principle in this face detection system. According to the hardware conditions, I analysis and list the current methods of face detection, choosing skin-color detection method as the basic means. In the image pre-processing stage, using the illuminated compensation technique compensates the brightness component of the video, which improved the accuracy for later algorithms greatly. A skin-color detection algorithm based on YUV color space is present. Through clustering analysis the human face in the YUV color space, construct the YUV color model to detecte the human face. The result shows that this model can effectively detect the color face in the image area, building a solid foundation for the rough location of the human face. Taking into account the operation of the system on the fly, the algorithm of the opening and closing operation is used to remove salt and pepper noise. On the basis of the former steps, if there exists the non-face areas in the binary image, the human face area would be affirmed via the marking connected-components algorithm. Finally, horizontal and vertical projection with regard to the black pixels determines the person’s eye region and cut off the human face.These algorithms will be run in DSP system platform.The results show that the system can accurately detect human faces, and satisfy the requirements of real-time system. If the technology of the face detection combines with the traditional video surveillance systems, it is able to promote the intelligence level of the traditional system. And the base of the Consequent development of human-machine interaction technique would be established.