基于机器视觉的芯片字符识别系统
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桂林理工大学 机械与控制工程学院 桂林 541006

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TP391.41;TN40

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国家自然科学基金地区基金(52065016)项目资助


Chip character recognition system based on machine vision
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College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China

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    摘要:

    IC芯片表面的字符主要包括厂商名称和序列号,这些字符对于芯片的制造和应用具有重要现实意义,针对芯片表面印刷字符的检测,基于HALCON视觉软件开发平台研发了一套芯片字符识别系统。首先,采用灰度值投影法获得字符区域的行和列坐标分割点,进行字符分割。然后,利用形状匹配技术对欲检测芯片图像进行定位与校正,采用BP神经网络分类算法实现字符的识别。通过不同算法的对比实验分析,实验结果表明单张图片检测时间为42 ms,完整字符与缺陷字符的分割准确率均为100%,字符识别率达到99.5%。本系统能有效快速、准确的对IC芯片表面字符进行识别,检测精度满足要求。

    Abstract:

    The characters on the surface of IC chip mainly include the manufacturer's name and serial number. These characters are of great practical significance for chip manufacturing and application. For the detection of printed characters on the chip surface, a chip character recognition system is developed based on Halcon visual software development platform. Firstly, the gray value projection method is used to obtain the row and column coordinate segmentation points of the character region for character segmentation. Then, the shape matching technology is used to locate and correct the chip image to be detected, and the BP neural network classification algorithm is used to realize character recognition. Through the comparative experimental analysis of different algorithms, the experimental results show that the detection time of a single picture is 42ms, the segmentation accuracy of complete characters and defective characters is 100%, and the character recognition rate is 99.5%. The system can effectively, quickly and accurately recognize the characters on the surface of IC chip, and the detection accuracy meets the requirements.

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杨桂华,唐卫卫,戴志诚,卫嘉乐.基于机器视觉的芯片字符识别系统[J].电子测量技术,2022,45(5):105-110

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  • 在线发布日期: 2024-05-30
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