朱柯润, 田丹. 基于机器视觉的电池尾端破皮检测[J]. 微电子学与计算机, 2014, 31(5): 117-120.
引用本文: 朱柯润, 田丹. 基于机器视觉的电池尾端破皮检测[J]. 微电子学与计算机, 2014, 31(5): 117-120.
ZHU Ke-run, TIAN Dan. Detection of the Broken Skin of the Battery Cathode Based on Machine Vision[J]. Microelectronics & Computer, 2014, 31(5): 117-120.
Citation: ZHU Ke-run, TIAN Dan. Detection of the Broken Skin of the Battery Cathode Based on Machine Vision[J]. Microelectronics & Computer, 2014, 31(5): 117-120.

基于机器视觉的电池尾端破皮检测

Detection of the Broken Skin of the Battery Cathode Based on Machine Vision

  • 摘要: 随着自动化生产的不断进步,人工操作在生产线上日渐减少,机器视觉应运而生,它具有速度快,精度高,连续工作时间长等特点.对于电池尾端的伤痕线上检测目前采用的是人工检测,效率和精度低下;因此提出了一种电池尾端破皮检测方法,将电池尾端图片二值化后,进行形态学处理,而后通过连通区域的个数来统计得出结论.此法不采用复杂的频谱分析,而采用形态学方法来消除噪点,达到判别伤痕的目的.这种方法大大减少了运算量,提高判别效率.

     

    Abstract: With the advances in automated production,manual operation decreasing fast in the production line,and machine vision come into being.It has high speed,precision,long running time and other characteristics.For the detection of the wounds of the bottom of the battery,we are currently using manual inspection,which has low efficiency and precision.This paper presents a method to detect the wound of broken skin of the battery bottom.We binarize the picture of the battery,and then to use morphological process.Finally we draw conclusion by counting the number of connected regions.This method does not use complex spectral analysis,and use morphological methods to eliminate noise,to achieve the purpose of discriminating wounds.This method greatly reduces the amount of computation to improve determination efficiency.

     

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