基于机器视觉的条形码定位方法研究与设计

Research and Design of Bar Code Location Method Based on Machine Vision

随着“中国智能制造”战略的实施,企业开始朝着大型、高效的智慧工厂发展。条形码以其高可靠性和低成本的优点,解决了工业管理中数据采集的问题,成为智慧工厂实现信息自动化、智能化和数据化的关键。为了对工业生产线上的产品标签条码进行高效识别和分拣,需要采用机器视觉方法和数字图像处理技术,对条形码先进行定位再进行识别。本文设计了一种基于机器视觉的条码位置定位技术。针对生产线上位置不同、大小不一的条码图像,采用Scharr算法边缘处理灰度图像,并对边缘检测结果二值化后滤波,经过形态学处理后定位出条码的位置。此方法对于清晰的条形码图片,摆正图片的定位率可以达到99%,倾斜图片的定位率也可达到97%,一张条形码定位用时100ms左右,满足现代大型、高效、集成的工厂的相关需求。

With the implementation of the"China Intelligent Manufacturing"strategy,enterprises began to develop towards large and efficient smart factories.With the advantages of high reliability and low cost,bar code solves the problem of data acquisition in industrial management.It is the key to realize information automation,intelligence and data in smart factory.In order to efficiently identify and sort the product label bar codes on the industrial production line,it is necessary to use machine vision and digital image processing technology to locate the bar codes first and then identify them.This paper designs a bar code location technology based on machine vision.Aiming at the bar code images with different positions and sizes on the production line,the Scharr algorithm is used to process the gray image,binarize and filter the edge detection results,and locate the position of the bar code after morphological processing.For clear bar code pictures,the positioning rate can reach 99%,and the recognition speed also meets the needs of modern large-scale and efficient integrated factories.