基于像素点的机器视觉系统能力评价
首发时间:2017-06-16
摘要:有效评价机器视觉测量系统能力,结合图像处理技术,提出了对于拍摄对象为形似矩形或形似椭圆形的不规则形状产品的机器视觉系统一般性能力评价方法。对获取的原始图像数据进行降噪、灰度处理、图像分割技术处理后得到图像目标区域及背景区域,以目标区域即不规则形状产品,所占像素点的个数及区域边界像素点个数,作为判断该产品是否合格的质量特性,并分析对其质量特性的可能影响因素,进行机器视觉测量系统分析,评价机器视觉系统的能力。通过案例分析表明,该方法能有效且准确评价机器视觉系统能力。
关键词: 机器视觉系统 图像处理技术 像素点个数 形似矩形或形似椭圆形的不规则形状产品
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A Research on Machine Vision System CapabilityEvaluation Based on Pixels
Abstract:For the effective evaluation of machine vision measurement system, Imaged processing technology was used to evaluate the capability of machine vision system (MVS), which is used to take photos of irregular products similar to the rectangular or oval. The original image data are processed by noise reduction, grayness and image segmentation technology to divide image into two parts, target region and background region. The number of pixels and the number of pixels at the boundary of the target region are considered as quality characteristics to determine whether the product is qualified or not, with the possible factors affecting its quality characteristics, the capability of MVS can be evaluated. A case is given to illustrate this method is more efficient and accurate.
Keywords: machine vision system image segmentation technology the number of pixels irregular products similar to rectangular or oval
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