Research On Design And Implementation Of Video Acquisition System Based On FPGA

As an important field of the Video image processing, the moving objects detection hasbeen wildly applied to variety applications, such as defense, security, industrial, transportationand medical. Therefore, the research of moving objects detection with real-time and highprecision is very useful to the actual application.At present, the majority of the motion detection system is implemented with the highperformance computer and the corresponding programming software. This method is not onlyexpensive, but also has large volume and small range of application. The FPGA is a kind ofparallel processing platform, which has the advantages of fast speed and good, and is verysuitable for video image processing and real-time. Based on the characteristics of the real-time moving object detection system and the advantages of FPGA, the real-time movingobject detection system implemented with FPGA is proposed in this paper.In this scheme, the real-time moving object detection system based on FPGA consists ofthe image acquisition module, the image cache module, the image processing module and theimage display module. The image acquisition module is composed of the I2C communicationsub-module and the THDB-D5M camera configuration sub-module, which can realize thereal-time image acquisition. The image cache module is composed of synchronous dynamicrandom access memory SDRAM, which can store the image frame with high speed. Theimage processing module includes five sub-modules, such as the RGB conversion module, theimage processing module, the Sobel edge detection module, the frame difference method ofmotion detection module and the two value morphology processing module. Finally, thedetection results are outputted and displayed by the image display module.Each module and the whole system are tested in actual experiments. The experimentalresults confirm that each module can work rightly, and the real-time moving object detectionsystem based on FPGA can detect the real-time moving object.