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摘 要随着机械加工技术的发展，企业单位对砂纸的需求量越来越大。传统的人工检测在砂纸检测中有很大局限性，给产品的质量控制带来了很多不稳定和不可靠的因素。那么能够在生产过程中及时检测出问题就成了一个很大的课题。我们急需要一种方法能够及时准确的检测出缺陷。59620
本文分析了砂纸缺陷在线检测系统中图像采集的摄像机和光源。确定并搭建了针对砂纸缺陷检测的硬件系统。考虑到缺陷的多样性，系统中综合采取了透射和漫反射的照明方式来采集图像信息。在分析并且对比各种图像算法优缺点的基础上，采用了自适应阈值分割的算法。实现了刮痕、堆砂和脱砂等缺陷的特征提取。最后，系统实现了检测缺陷的面积、周长、长度等参数。对砂纸缺陷定量分析。
论文算法都在matlab7.0编程环境下进行编写仿真。实践证明系统和算法可以满足图像检测实时性的要求。
毕业论文关键词 图像处理 缺陷检测 缺陷识别
毕业设计说明书（论文）外文摘要
Title Sandpaper defect detection technology
Abstract With the development of machining technology, the demands for sandpaper are increasing in enterprises. There are many limitations in the traditional manual inspection in sandpaper detection , which bring a lot of instability and unreliability factors to the control of product quality Then it has become a big issue to be able to find out the problemsb during the production process .We urgently need a way to be able to detect the defects timely and accurately.
This paper analyzes The image capture camera and light source for the sandpaper defect detection system are analyzed in this paper. Hardwares for sandpaper defect detection system are also be identified and built . A comprehensive transmission and diffuse lighting methods have been adopted to capture image information in the system，taking the persity of defects into account . Adaptive threshold segmentation algorithm has been used on the basis of the analysis and comparison of the advantages and disadvantages of the various algorithm .Feature extraction for defects such as scratches, sand on and sand off are also be realized . Finally, the detection of defects in the area, perimeter, length and other parameters are realized by the system, as well as the quantitative analysis of defects on sandpaper.
The algorithms in the thesis are simulated under the programming environment of matlab 7.0 .Practice has proved that the real-time requirements can be met by the image detection system and algorithms .
Keywords Image Procession Defect Detection Defect Recognition
目 录
1.绪论 5
1.1砂纸缺陷种类 5
1.2砂纸的制作工艺及其检测现状 6
2.图像处理的相关原理 7
2.1图像变换 7
2.1.1傅里叶变换： 7
2.1.2沃尔什-阿达玛变换： 7
2.1.3离散卡夫纳－勒维变换： 7
2.2图像显示 8
2.2.1灰度变换 8
2.3图像增强和复原 8
2.3.1中值滤波 8
2.4图像分割 9
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