KEYWORDS: Field programmable gate arrays, Image processing, Digital signal processing, Manufacturing, Control systems, Telecommunications, Imaging systems, Image transmission, Image acquisition, Signal processing
Compared with the recognized standard precision measuring instrument laser interferometer, grating scale measurement has been widely used in industry because of its advantages of low price, high resolution and high precision. In the measurement system with a grating ruler as a sensor, displacement accuracy and real-time performance are important indexes to measure the whole system's performance. This paper presents a real-time displacement measurement system of FPGA grating ruler based on image processing. The system includes a grating ruler motion platform built by a high-speed camera, an integrated processing board for image processing, a macro-micro composite displacement calculation based on FPGA, and a human-computer interface. FPGA has the characteristics of high-speed real-time data acquisition and parallel processing, and can realize high-speed image acquisition and processing. Coupled with the robust image data transmission and storage ability of high-speed image capture cards, the FPGA displacement measurement system based on image processing can meet the real-time processing and displacement measurement under the condition of high-speed acquisition. In this paper, the real-time performance of the system is verified by processing and Simulation of the collected images.
With the gradual miniaturization of microelectronic products, the requirements of enterprises for code encoding and decoding of their products continue to increase. This paper takes the micro anti-counterfeiting code as the research object and designs a set of micro-feature recognition equipment based on machine vision technology and an automatic threshold algorithm via different light intensity and interference. The equipment is composed of industrial cameras, auxiliary light sources, and three-axis fine-tuning modules. In order to collect typical micrographs with characteristic size in the range of 50-200μm. The algorithm uses the local gray features of the anti-counterfeiting code to perform a bilateral threshold to remove the false and inferior edges and eliminate the light intensity influence on the image threshold by fitting the relationship formula between the pixel value and the gamma transformation. Based on the images collected in actual production, the applicable recognition rate based on 5335 samples is as high as 99.5%, with a particular application value in microscopic anti-counterfeiting detection.
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