本文選題：機器視覺 + 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)量檢測作為印刷生產(chǎn)過程中的必要環(huán)節(jié),其檢測技術(shù)的創(chuàng)新與發(fā)展對于傳統(tǒng)印刷業(yè)變革具有重要的現(xiàn)實意義。為了有效提高印刷質(zhì)量檢測的自動化程度,本文在機器視覺和數(shù)字圖像處理的基礎(chǔ)上,綜合運用光源照明、傳感器、光學(xué)成像、軟件開發(fā)等知識,研究一種印刷質(zhì)量的圖像檢測技術(shù)。通過采用模塊化設(shè)計開發(fā)印刷質(zhì)量檢測系統(tǒng),為解決實際印刷過程中存在的檢測效率低、穩(wěn)定性差等問題提供了可行性方案。基于系統(tǒng)組成和算法設(shè)計兩個方向,本文詳細(xì)闡述了印刷質(zhì)量的圖像檢測技術(shù)在包裝印刷領(lǐng)域的應(yīng)用和系統(tǒng)實現(xiàn)。本課題的主要研究內(nèi)容如下:(1)針對實際生產(chǎn)需要,通過分析機器視覺原理及其應(yīng)用,合理確定系統(tǒng)硬件設(shè)備選型方案,設(shè)計了一套由傳送帶、LED光源、CCD工業(yè)相機、光電開關(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,系統(tǒng)利用Pylon Viewer程序驅(qū)動相機自動完成對印刷品準(zhǔn)確拍攝。針對外界光照對圖像采集過程的影響,本裝置對相機和光源進行密封操作,從而保證后續(xù)圖像處理時能夠獲得高質(zhì)量的印刷圖像。(2)為確保系統(tǒng)順利實現(xiàn)印刷圖像自動檢測過程,根據(jù)印刷檢測的技術(shù)要求,本文提出了一系列印刷圖像處理識別相關(guān)算法,主要包括圖像預(yù)處理、圖像配準(zhǔn)和缺陷分類識別三大類。在印刷圖像預(yù)處理過程中,本文對圖像灰度化、圖像增強、圖像分割等關(guān)鍵算法詳細(xì)介紹,為后續(xù)檢測結(jié)果的準(zhǔn)確性提供保障。根據(jù)不同類型印刷品特點,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,為進一步缺陷識別奠定良好的基礎(chǔ)。針對檢測系統(tǒng)的功能需求,本文設(shè)計缺陷目標(biāo)提取與分類識別算法,同時通過改進多類支持向量機完成印刷缺陷的自動識別與分類。最后,本文基于C++編程語言,利用Visual Studio 2013開發(fā)工具,綜合運用編程和軟件項目開發(fā)知識,實現(xiàn)印刷質(zhì)量檢測系統(tǒng)可視化平臺。
[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)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TS807;TP391.41

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