| In the era of big data,faced with a large number of data,we need to use high-speed dedicated chips to deal with data to solve some specific problems.FPGA which can process data at high-speed applied to many high-speed systems.Image extraction is an important method of information processing.Edge detection distinguishes the information contained in the image by the luminance component of the image,including pixel continuity,data variation and background changes in the image.The extracted information is output through image matching which can be achieved by the correlation of images,the feature matrix and the like.When the weather is bad or the visibility is low,the accuracy of target recognition will be affected.In response to this problem,an improved edge detection algorithm based on the performance advantages of FPGA is proposed and its effectiveness is validated in this paper to improve the target recognition rate and the ability to process data.All the algorithms are programmed on the EP4 CE chip.The main ideas of the paper are as follows:(1)Firstly,a detailed scheme of the system and the related algorithms are analyzed and researched.The image information recognition is realized by edge detection,character segmentation,feature extraction and template matching.(2)Common edge operators and new edge detection algorithms are introduced.An improved edge detection algorithm based on FPGA performances is proposed in the paper.Software simulations are compared and hardware operations are achieved.The results show the improved algorithm performs better than the original one.(3)The overall FPGA system structure is designed.The clock module,the image acquisition module,the image gray processing module,the image edge detection module,the image segmentation,the target information extraction and the result display are implemented.The system can extract the information from the collected images and is of practical significance in the field of image information high-speed extraction. |
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