摘要:随着社会的平稳发展,人民生活水平的提高,食品安全越来越受到民众的关注,产品的生产质量也成了生产厂商和供应商所关注的焦点。巨大的市场需求促使矿泉水、果汁等众多的食品饮料产业飞速的发展,而饮料瓶封装质量的好坏直接影响着饮料本身的质量安全问题。利用机器视觉的图像检测技术来鉴定饮料瓶的封装完好情况能大幅度降低检测成本,提高产品质量,加快生产速度和效率,节约成本。因此,对于高效低廉的图像检测系统的研究是具有实际意义的。35578
对于工业生产检测领域来说,同时具备精度高、可靠性强和实时性好的检测技术一直是人们不懈努力追求的目标。本文研究了基于图像匹配的饮料瓶封装缺陷检测技术。首先介绍了图像中的直线检测算法和非直线检测算法;然后根据实际检测要求,实现了基于MATLAB的仿真软件,并进行了仿真实验验证。
毕业论文关键词:图像匹配;图像检测;hough变换;边缘检测算法
Based on machine vision product testing
Abstract:With the steady development of the society, the improvement of people's living standards, food safety more and more get the attention of people, the production quality has become the focus of manufacturers and suppliers. The huge market demand is driving the mineral water, fruit juice, and many other food and beverage industry rapid development, and beverage bottle packaging quality directly influences the quality of the drink itself safety problems. Using machine vision image detection technology to identify beverage bottle packaging in good condition to reduce the cost of test, improve product quality, to speed up the production speed and efficiency, cost savings. Therefore, for the study of low efficient image detection system is a practical significance.
For industrial production inspection field, at the same time with high precision, high reliability and good real-time performance detection technology has been unremitting efforts to the pursuit of the goal. This paper studies the beverage bottle packaging defects detection based on image matching technology. First introduced the image in a straight line detection algorithms and non linear detection algorithm; Then according to the actual testing requirement, realized based on MATLAB simulation software, a simulation experiment was carried out.
KeyWords: Image Matching ;Image Detection ;Hough Transformation ;Edge Detection Algorithm
目录
1 绪论. 1
1.1 课题背景及研究意义 1
1.1.1 课题背景.1
1.1.2 课题研究意义.2
1.2 国内外研究现状和水平 2
1.3 发展趋势 3
1.4 本文研究的主要内容 4
2 常用图像的基本几何图形的检测技术 5
2.1 直线检测技术及其优缺点 5
2.2 圆检测技术及其优缺点 5
2.3 椭圆检测技术及其优缺点 6
3 图像处理 8
3.1 二值图像 8
3.2 灰度图像 8
3.3 RGB彩色图像 9
3.4 图像增强和复原 9
3.4.1 图像增强 9
3.4.2 图像复原 9
3.5 图像分割 10
3.6 图像压缩 11
3.7 图像分析 11
4 图像检测算法 13
4.1 边缘检测法 13
4.2 阀值分割法 14
5 Hough变换检测基本几何图形原理 15
5.1 Hough变换检测直线的原理 15
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