机器视觉系统在桔瓣质量检测中的应用

开发了一套罐装线实时在线质量检测视觉系统，用于装罐前桔瓣上头发等细长形杂质检测，以保证产品质量。硬件系统采用了6台彩色CCD摄像头，两台计算机的处理结构。软件系统依据杂质和背景在颜色分布及形状大小等特征上的差异进行分离，其核心是一种用于二值图像特征区域提取的新型连通算子—面积重构算子，利用该算子平滑图像时不破坏对象轮廓完整的优点，结合改进的区域生长、区域消减等算法，形成了一套完整的检测算法。试验显示系统处理能力约30片/s，错误率仅2%。该系统能满足实时生产准确性和在线处理的要求，为其实用化、商品化奠定了基础。

Application of machine vision inspection system for orange petal quality detection

A machine vision inspection system for realtime on-line inspection was developed, which aimed at the detection of impurities on orange petals before canned, such as hairs and fibriform objects. The hardware system was mainly made up of six CCD cameras and two computers. The software system was developed to separate the impurities from the orange sections by the color and shape feature. Some algorithms including region growing, area-reconstruction operator were used. Area-reconstruction was a new connected operator, which could preserve contours when simplifying the image. The system was able to inspect the orange petals at a rate of 30 petals/second and the inaccurate classification rate was only about 2%. The experimental results show clearly that the machine vision inspection system reaches two main objectives: accurate feature extraction and on-line treatment capabilities and can be adopted for further commercial utilization.