Research And Design Of Image Edge Detection System Based On FPGA

With the development of the times,electronic detection systems have been integrated into people's daily production and life,and target recognition and detection technology has been widely used in transportation,industry,medical aviation and other fields.Image edge detection technology is the basic technology of target recognition.The edge detection effect directly affects the success of target recognition results.With the increasing amount of data collected by images,the disadvantages of traditional computers,such as high energy consumption,slow data processing speed,and long delay,can no longer meet people's requirements for high-speed and accurate edge detection.The FPGA processor has the advantages of parallel data processing,low latency,and low power consumption,and is suitable for processing large amounts of image data.This design is an image edge detection system based on FPGA processor.The design content mainly includes building a hardware platform,dividing the system's functional modules,designing image preprocessing related algorithms,algorithm hardware transplantation and implementation.The design achievements are as follows:(1)Combined with the development board of the FPGA processor,the OV7670 camera and the display driven by VGA,a hardware platform for the image edge detection system is built,the image information is collected by the camera and the data is transmitted to the FPGA development board for data storage and processing Data is transferred to the display screen through the VGA driver.(2)The functional module is mainly divided into OV7670 camera acquisition module,SDRAM storage module and VGA display module in hardware.The storage module uses the ping-pong operation design to solve the frame interlacing phenomenon.The functional module is mainly divided into the defogging algorithm,sobel algorithm,Gaussian filtering algorithm and binary conversion,etc.The defogging algorithm is an innovation of this design,which mainly uses the dark channel defogging algorithm to defog the image To improve the detail and color of the image;the sobel operator is used because it incorporates the idea of gradient weighting,and it is not as complicated as the second-order algorithm.(3)The algorithm is transplanted in hardware,each functional module is written in Verilog language,and then each functional module is simulated and verified by Questa sim.After verification of the simulation timing,each module is compiled and integrated with Quartus ?,and the The integrated file is burned to the development board.(4)By observing the experimental results,it is found that the edges detected by the image processed by the defogging algorithm are more obvious,and the details are more prominent.The threshold of the system can be adjusted.In the case of different thresholds,the obtained edge detection effects are different,and the most suitable threshold is set by comparing the edge detection effects.