节点文献

LED晶粒分拣技术的机器视觉研究

Machine Vision Research on Technology of LED Die Sorting

【作者】 马瑶

【导师】 张海宁;

【作者基本信息】 西安工业大学 , 通信与信息系统, 2010, 硕士

【摘要】 LED晶粒的分拣是LED生产中的一个重要环节,由于分拣设备长久以来一直被国外市场垄断,所以研发具有自主知识产权的LED分拣设备势在必行。而作为分拣设备中,机器视觉技术又是至关重要的,它设计的好坏直接影响着整个分拣的系统。本文主要研究机器视觉技术在LED分拣设备中的应用。论文以高速CCD相机、镜头、图像采集卡及工控机为核心组件,构建了基于机器视觉的硬件平台,用来对图像进行采集与处理。在LED分拣设备中,晶粒的位置信息是至关重要的,它为整个的分拣工作提供了基本参数信息。为了得到LED晶粒的位置参数,论文中采用了基于区域灰度值的模板匹配算法。深入分析了模板匹配算法的功能及预处理的过程。在相应的匹配工作基础上要对图像进行区域的分割,进而改变图像的表示方法,并对图像像素进行再组织,形成更高级的表示单元。区域分割是一个集合划分的过程,它只是把相似的像素划分到不同的区域中,分割得到的区域仍然有很多冗余信息为了消除这些冗余信息,在此提出了感兴趣区域来描述图像。它可以增强图像对比度,能显著的描述物体的轮廓和形状,并在一定程度上消除了图像的冗余信息,突出图像的主要内容。CCD在拍摄过程中,由于光学镜头存在有一定的光学畸变,将会引入一定的测量误差,从而影响晶粒的识别和定位。为了解决这一问题,本文提出采用预处理前对图像进行校正的措施来消除畸变。识别完成后会生成LED位置信息的参数表,该表为运动控制提供了运动数据。本课题以VC++6.0作为软件开发平台,使用Sapera Processing图像处理软件来实现开发LED分拣设备的机器视觉的软件控制系统。利用机器视觉的处理算法来实现图像的识别与定位。经过测试结果表明,论文中所构建的硬件平台及机器视觉处理算法合理,且处理精度达到生产精度的要求,具有很好的实用性。

【Abstract】 The Sorting of LED is one of the most components of the LED production. In the past, sorting equipment has been monopolized by foreign companies; therefore, it’s extremely urgent and necessary to develop LED sorting equipment with independent intellectual property rights. In sorting equipment, machine vision technology is of paramount important, whose design have a significant impact on the whole sorting system. This paper mainly focused on the application of machine vision technology into LED sorting equipment.The machine vision hardware platform is established to gather and process image base on high-speed CCD camera, lens, image acquisition card and industrial control computer in this paper. In the LED sorting equipment, the dies location information is essential and works for the entire basic parameter information. The template matching algorithm based on gray value of region was developed to determine the LED dies’ level and location parameters. This study further analyzed the function and pretreatment process of the template matching algorithm. Before the corresponding matching, the image was regionally segmented. The main objective of segmentation was to divide the image into small components, change the way of image presentation and to re-organize image pixels to form a more advanced unit, which was also useful to facilitate in-depth analysis. Regional segmentation was only a partitioning process; and it only put similar pixels into different regions; As a result, there were still much redundant information after segmentation. Therefore, we would like to describe the image with regions of interest (ROI). ROI refers to the image region which can arouse the interest of the most users’ and is able to well present main image content; it can exactly show the profile and shape of the objects; it can eliminate redundant image information in a certain extent and highlight the core content of the image. Because optical distortion that caused by lens affect the identification and positioning of dies when CCD is working. To solve this problem, the measure of pre-process was applied before the image correction. After identification, it will generate LED location parameter table, which provides for the motion control the movement of data. Base on VC + +6.0 as a software development platform, Sapera Processing image processing software was applied to develop the software control system of machine vision for LED sorting equipment. Machine vision processing algorithms was developed to achieve the image recognition and location. The test results show that the hardware platform and visual processing algorithms in this study are reasonable, and the processing accuracy can meet the requirements of production. The system has good practicability and utility.

节点文献中: 

本文链接的文献网络图示:

本文的引文网络