摘要目前，在我国的啤酒行业包装还是以玻璃酒瓶为主，啤酒产商为了控制成本，提高自己的经济利益，都会对啤酒瓶进行回收利用。然而，在这一过程中酒瓶不可避免的有碰撞、损耗，特别是在瓶口容易产生缺口、毛刺等，这样的啤酒瓶会为今后的使用留下安全隐患。59998
传统的检测方法一般是利用特定的光线照射后的形成的反射效果来判断啤酒瓶是否有缺陷，这种检测方法在速度和精度上都达不到技术要求，这样的检测方式不能满足现代化快节奏的生产方式。机器视觉具有速度快、精度高、信息处理量大等多重优点，这样可以客服传统检验方式的不足，实现了自动化快速检测，大大提高了生产效率。
CCD器件有着精确的像素间距，通过对测试图像成像，后期再经过算法处理可以方便、快捷、精确的检出有缺陷的物件。本课题就是利用CCD成像器件，结合简单的图像处理与MATLAB，实现在线的啤酒瓶缺陷检测。
毕业论文关键词：CCD成像器件 缺陷检测 图像处理 自动模式识别
毕业设计说明书（论文）外文摘要
Title Workpiece defect detection based on CCD
Abstract
In China 's beer industry, packaging or mainly beer bottles , beer producers in order to control costs and improve their own economic interests are beer bottles for recycling . Bottle However, in this process inevitably there is a collision , loss such as nicks, burrs, easy to produce , especially in the bottle , this beer bottles will be a security risk for a future use .
The traditional method of detecting ships is the use of a lot of light irradiation after the formation of the reflection effect to determine the beer bottle is defective , such detection methods are lower than the technical requirements in terms of speed and accuracy , with the rapid development of electronic technology and computer this detection method can not meet the fast-paced modern production methods . In recent years , machine vision continuous development , improvement and industrial applications , it has a fast , high precision , large amount of information processing , such as multiple advantages , so customer service deficiencies of the traditional inspection , automated rapid detection , greatly improving the production efficiency.
CCD device with precise pixel pitch, the test image imaging late after algorithm processing can be convenient, fast and accurate detection of defective objects . This topic is the use of a CCD imaging device , combined with simple image processing with MATLAB , the online beer bottle defect detection .
Keywords: CCD imaging device defect detection image processing automatic pattern recognition
1 绪论 2
1．1 课题的目的与意义 3
1．3 本论文研究的内容介绍 5
2 成像装置硬件设计 6
2．1 成像装置结构示意图 6
2．2 照明方式的选择设计 7
2．3 各部分器件选择 8
3 图像处理部分 10
3．1 图像增强基本技术 10
3．2 啤酒瓶图像的滤波方法比较 13
3．3 图像分割技术 15
3．4 瓶底反光区域消除 19
4 缺陷自动识别 基于CCD的工件缺陷检测:http://www.youerw.com/wuli/lunwen_65340.html