基于机器视觉的啤酒瓶检测系统研究

为了提高啤酒瓶的检测效果,提出了一个基于机器视觉的啤酒瓶检测系统的方案.根据啤酒瓶检测过程的高速度、高精度和实时性的特点,设计了系统中图像获取、图像处理和图像识别的过程和方法.利用图像滤波去除获取的啤酒瓶数字图像中的噪声,通过二值化将物体和背景分离,再经过边缘检测提取边缘,最后识别和分类有缺陷的啤酒瓶.实验结果表明,该方案能够快速有效地对啤酒瓶进行检测,提高了检测效果,具有一定的可行性和现实意义.

Research on beer bottle detection system based on machine vision

To improve the effect of beer bottle detection,a program of beer bottle detection system based on machine vision is presented.Based on the high-speed,high precision and real-time characteristics of the detection process,the process and the methods of image acquisition,image processing and image recognition are designed.Firstly,the noise in the digital images of beer bottles acquired is removed by filtering.Secondly,the object and the background of the images are separated after binarization.Then,the edges of the images are extracted through edge detection.Finally,the beer bottles with defects are identified and classified.Experiments show that the program could detect beer bottles quickly and improve detection effect with a certain feasibility and practical significance.