本文選題：機(jī)器視覺(jué) + 圖像處理��； 參考：《華東理工大學(xué)》2017年碩士論文

【摘要】：在制造業(yè)轉(zhuǎn)型升級(jí)背景下,印刷業(yè)面臨傳統(tǒng)技術(shù)改造的難題。質(zhì)量檢測(cè)作為印刷生產(chǎn)過(guò)程中的必要環(huán)節(jié),其檢測(cè)技術(shù)的創(chuàng)新與發(fā)展對(duì)于傳統(tǒng)印刷業(yè)變革具有重要的現(xiàn)實(shí)意義。為了有效提高印刷質(zhì)量檢測(cè)的自動(dòng)化程度,本文在機(jī)器視覺(jué)和數(shù)字圖像處理的基礎(chǔ)上,綜合運(yùn)用光源照明、傳感器、光學(xué)成像、軟件開(kāi)發(fā)等知識(shí),研究一種印刷質(zhì)量的圖像檢測(cè)技術(shù)。通過(guò)采用模塊化設(shè)計(jì)開(kāi)發(fā)印刷質(zhì)量檢測(cè)系統(tǒng),為解決實(shí)際印刷過(guò)程中存在的檢測(cè)效率低、穩(wěn)定性差等問(wèn)題提供了可行性方案�；谙到y(tǒng)組成和算法設(shè)計(jì)兩個(gè)方向,本文詳細(xì)闡述了印刷質(zhì)量的圖像檢測(cè)技術(shù)在包裝印刷領(lǐng)域的應(yīng)用和系統(tǒng)實(shí)現(xiàn)。本課題的主要研究?jī)?nèi)容如下:(1)針對(duì)實(shí)際生產(chǎn)需要,通過(guò)分析機(jī)器視覺(jué)原理及其應(yīng)用,合理確定系統(tǒng)硬件設(shè)備選型方案,設(shè)計(jì)了一套由傳送帶、LED光源、CCD工業(yè)相機(jī)、光電開(kāi)關(guān)、旋轉(zhuǎn)編碼器和PLC控制器組成的印刷圖像采集裝置。在采集印刷品圖像時(shí),系統(tǒng)利用Pylon Viewer程序驅(qū)動(dòng)相機(jī)自動(dòng)完成對(duì)印刷品準(zhǔn)確拍攝。針對(duì)外界光照對(duì)圖像采集過(guò)程的影響,本裝置對(duì)相機(jī)和光源進(jìn)行密封操作,從而保證后續(xù)圖像處理時(shí)能夠獲得高質(zhì)量的印刷圖像。(2)為確保系統(tǒng)順利實(shí)現(xiàn)印刷圖像自動(dòng)檢測(cè)過(guò)程,根據(jù)印刷檢測(cè)的技術(shù)要求,本文提出了一系列印刷圖像處理識(shí)別相關(guān)算法,主要包括圖像預(yù)處理、圖像配準(zhǔn)和缺陷分類(lèi)識(shí)別三大類(lèi)。在印刷圖像預(yù)處理過(guò)程中,本文對(duì)圖像灰度化、圖像增強(qiáng)、圖像分割等關(guān)鍵算法詳細(xì)介紹,為后續(xù)檢測(cè)結(jié)果的準(zhǔn)確性提供保障。根據(jù)不同類(lèi)型印刷品特點(diǎn),本文提出兩種基于ROI模板及基于Hough和Fourier變換的印刷圖像配準(zhǔn)算法,為進(jìn)一步缺陷識(shí)別奠定良好的基礎(chǔ)。針對(duì)檢測(cè)系統(tǒng)的功能需求,本文設(shè)計(jì)缺陷目標(biāo)提取與分類(lèi)識(shí)別算法,同時(shí)通過(guò)改進(jìn)多類(lèi)支持向量機(jī)完成印刷缺陷的自動(dòng)識(shí)別與分類(lèi)。最后,本文基于C++編程語(yǔ)言,利用Visual Studio 2013開(kāi)發(fā)工具,綜合運(yùn)用編程和軟件項(xiàng)目開(kāi)發(fā)知識(shí),實(shí)現(xiàn)印刷質(zhì)量檢測(cè)系統(tǒng)可視化平臺(tái)。
[Abstract]:Under the background of manufacturing industry transformation and upgrading, the printing industry faces the difficult problem of traditional technology transformation. As a necessary link in the process of printing production, the innovation and development of quality inspection technology is of great practical significance to the traditional printing industry. In order to improve the automation of printing quality inspection effectively, this paper, on the basis of machine vision and digital image processing, synthesizes the knowledge of light source lighting, sensor, optical imaging, software development, etc. An image detection technique for printing quality is studied. A printing quality inspection system is developed by modular design, which provides a feasible scheme for solving the problems of low detection efficiency and poor stability in the actual printing process. Based on the two directions of system composition and algorithm design, this paper describes the application and system implementation of printing quality image detection technology in the field of packaging and printing in detail. The main research contents of this subject are as follows: (1) according to the actual production needs, through analyzing the principle and application of machine vision, reasonably determining the selection scheme of the hardware equipment of the system, designing a set of CCD industrial camera and optoelectronic switch with the LED light source of the conveyor belt. The printing image acquisition device composed of rotary encoder and PLC controller. When collecting print image, the system uses Pylon Viewer program to drive the camera to automatically complete the accurate shooting of printed matter. In view of the influence of outside illumination on the image acquisition process, the device seals the camera and light source to ensure that high quality printing image can be obtained in the subsequent image processing. According to the technical requirements of printing detection, this paper proposes a series of printing image processing recognition algorithms, including image preprocessing, image registration and defect classification recognition. In the process of printing image preprocessing, the key algorithms such as grayscale image, image enhancement, image segmentation and so on are introduced in detail in order to guarantee the accuracy of the following detection results. According to the characteristics of different types of printing materials, this paper presents two kinds of printing image registration algorithms based on ROI template and Hough and Fourier transform, which lay a good foundation for further defect recognition. In order to meet the functional requirements of the detection system, this paper designs an algorithm for the extraction and classification of defect targets. At the same time, an improved multi-class support vector machine (SVM) is used to realize the automatic recognition and classification of printing defects. Finally, based on C programming language and Visual Studio 2013 development tools, the visual platform of printing quality inspection system is realized by using the knowledge of programming and software project development.
【學(xué)位授予單位】：華東理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TS807;TP391.41

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