本文選題：機(jī)器視覺　切入點(diǎn)：圖像處理　出處：《杭州電子科技大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著工業(yè)自動(dòng)化發(fā)展,現(xiàn)代化生產(chǎn)過程對(duì)檢測(cè)方法、精度和速度提出了更高的要求。機(jī)器視覺檢測(cè)系統(tǒng)及技術(shù)的廣泛應(yīng)用符合工業(yè)自動(dòng)化發(fā)展的需要,能有效提高檢測(cè)的效率和精度,從而提高工業(yè)的自動(dòng)化程度。在橡膠輪胎的生產(chǎn)中,需要在線對(duì)胎面進(jìn)行長(zhǎng)度檢測(cè),現(xiàn)有的檢測(cè)方法大都采用人工在線抽樣檢測(cè)并記錄檢測(cè)結(jié)果,其檢測(cè)效率較低,檢測(cè)精度也不能得到有效保障。本文針對(duì)橡膠輪胎胎面生產(chǎn)線的要求,結(jié)合機(jī)器視覺檢測(cè)技術(shù),設(shè)計(jì)了一種輪胎胎面檢測(cè)系統(tǒng)。該系統(tǒng)可實(shí)現(xiàn)生產(chǎn)線上的橡膠輪胎胎面的幾何量(長(zhǎng)度和傾斜角度)、胎面字符等信息的在線檢測(cè)與識(shí)別,并將檢測(cè)結(jié)果實(shí)時(shí)保存到上位機(jī)數(shù)據(jù)庫(kù)。本文主要完成了以下工作:(1)對(duì)輪胎胎面檢測(cè)系統(tǒng)進(jìn)行總體方案設(shè)計(jì)。將檢測(cè)系統(tǒng)分為圖像采集、信息處理、信息執(zhí)行三個(gè)模塊,并進(jìn)行任務(wù)分配,對(duì)各模塊中的關(guān)鍵技術(shù)及基本原理進(jìn)行了闡述。(2)設(shè)計(jì)檢測(cè)系統(tǒng)的幾何量檢測(cè)方法�；跈C(jī)器視覺技術(shù),采用圖像預(yù)處理、閾值分割、胎面區(qū)域提取、邊緣檢測(cè)等方法實(shí)現(xiàn)了基于形狀特征的長(zhǎng)度檢測(cè)方法并進(jìn)行改進(jìn);設(shè)計(jì)了基于霍夫變換的傾斜角檢測(cè)方法;從檢測(cè)準(zhǔn)確率、檢測(cè)時(shí)間方面對(duì)方法的性能進(jìn)行了分析。(3)設(shè)計(jì)檢測(cè)系統(tǒng)的字符檢測(cè)方法�；跈C(jī)器視覺軟件和機(jī)器學(xué)習(xí)方法,通過圖像預(yù)處理、字符訓(xùn)練、字符分類器、字符識(shí)別等步驟實(shí)現(xiàn)字符檢測(cè);從檢測(cè)準(zhǔn)確率、檢測(cè)時(shí)間方面,分析了不同分類器對(duì)字符檢測(cè)的影響。(4)根據(jù)檢測(cè)系統(tǒng)的要求,結(jié)合下位機(jī)的通訊協(xié)議、MySQL數(shù)據(jù)庫(kù),在VS2010和Halcon平臺(tái)上進(jìn)行編程,實(shí)現(xiàn)檢測(cè)系統(tǒng)的完整功能。在檢測(cè)現(xiàn)場(chǎng)對(duì)該系統(tǒng)的準(zhǔn)確率、實(shí)時(shí)性和檢測(cè)精度進(jìn)行測(cè)試。
[Abstract]:With the development of industrial automation, modern production process has put forward higher requirements for testing methods, accuracy and speed. The wide application of machine vision inspection system and technology meets the needs of the development of industrial automation. Can effectively improve the efficiency and accuracy of the detection, thereby increasing the degree of industrial automation. In the production of rubber tyres, it is necessary to check the tread length online. Most of the existing detection methods use manual on-line sampling and record the test results, its detection efficiency is low, and the detection accuracy can not be effectively guaranteed. In this paper, according to the requirements of rubber tire tread production line, combined with machine vision detection technology, A tire tread detection system is designed, which can be used to detect and recognize the geometry of rubber tire tread (length and tilt angle, tread character, etc.) on line. The system is divided into three modules: image collection, information processing and information execution, and the system is divided into three modules: image collection, information processing and information execution. The key technology and basic principle of each module are described in detail. Based on machine vision technology, image preprocessing, threshold segmentation and tread area extraction are adopted. Edge detection and other methods have realized and improved the length detection method based on shape features, and designed a slope angle detection method based on Hough transform. Based on machine vision software and machine learning method, image preprocessing, character training, character classifier, Character recognition and other steps to achieve character detection, from the detection accuracy, detection time, analysis of different classifiers on character detection. 4) according to the requirements of the detection system, combined with the communication protocol of the lower computer MySQL database, The complete function of the detection system is realized by programming on the platform of VS2010 and Halcon, and the accuracy, real time and accuracy of the system are tested on the spot.
【學(xué)位授予單位】：杭州電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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本文編號(hào)：1606156