發(fā)布時(shí)間：2018-07-08 14:26

  本文選題：機(jī)器視覺 + 感興趣區(qū)域��； 參考：《山東大學(xué)》2015年碩士論文

【摘要】：隨著國(guó)內(nèi)外智能監(jiān)控行業(yè)和安防產(chǎn)業(yè)的發(fā)展,機(jī)器視覺越來(lái)越多地應(yīng)用在人體行為及表情識(shí)別、PCB印刷電路檢測(cè)、數(shù)字和指針儀表識(shí)別、產(chǎn)品外觀檢測(cè)、物流物品分類等諸多方面,機(jī)器視覺取代人工視覺進(jìn)入各種領(lǐng)域,大大提高了人們的生產(chǎn)生活效率。在工業(yè)領(lǐng)域中,各類儀表如聲級(jí)計(jì)、噪聲劑量計(jì)、震動(dòng)測(cè)量?jī)x、壓力表等在生產(chǎn)中發(fā)揮著重大的作用,這些儀表的示值讀取通常采用人工方式,效率低、受主觀影響比較大,極易產(chǎn)生誤讀,利用機(jī)器視覺來(lái)識(shí)別儀表示值非常有應(yīng)用價(jià)值�；�于上述形勢(shì)和問(wèn)題,本論文研究了機(jī)器視覺在儀表監(jiān)控識(shí)別系統(tǒng)中的應(yīng)用。論文首先介紹了機(jī)器視覺和儀表監(jiān)控識(shí)別系統(tǒng)的研究意義和發(fā)展現(xiàn)狀,接著對(duì)機(jī)器視覺各個(gè)組成部分做了詳細(xì)的介紹和選型方法總結(jié),然后分別介紹了本課題的硬件組成和軟件平臺(tái),最后通過(guò)軟件設(shè)計(jì)完成了對(duì)數(shù)字和指針式儀表識(shí)別的讀數(shù)識(shí)別,并對(duì)識(shí)別的效果做了總結(jié)。通過(guò)研究工業(yè)應(yīng)用中的幾種數(shù)字式和指針式儀表的監(jiān)控識(shí)別,本課題采用了具有優(yōu)質(zhì)性能的德國(guó)Basler工業(yè)攝像頭獲取圖像,借助于微軟的MFC、OpenCV、 pylon SDK開發(fā)工具實(shí)現(xiàn)系統(tǒng)的軟件設(shè)計(jì)。其中本課題的重點(diǎn)是儀表識(shí)別的算法設(shè)計(jì)。系統(tǒng)首先使用機(jī)器視覺方法采集儀表的圖像,然后利用數(shù)字圖像處理技術(shù)對(duì)圖像進(jìn)行預(yù)處理操作(使用加權(quán)平均法進(jìn)行灰度化、使用直方圖均衡化進(jìn)行圖像增強(qiáng)、進(jìn)行局部自適應(yīng)二值化、用開閉操作進(jìn)行形態(tài)學(xué)處理)；進(jìn)而根據(jù)數(shù)字儀表表盤上的位置、長(zhǎng)度、寬高比、輪廓等外觀特征信息提取示值區(qū)域,對(duì)指針儀表使用霍夫變換提取圓形輪廓、定位出指針區(qū)域；最后使用圖像分割技術(shù)將數(shù)字和指針?lè)指畛鰜?lái),采用自定義模板匹配方法識(shí)別出字符、霍夫線變換檢測(cè)出指針并計(jì)算讀數(shù)。通過(guò)實(shí)際場(chǎng)景下的測(cè)試,本系統(tǒng)的識(shí)別速度和識(shí)別準(zhǔn)確度均能夠達(dá)到應(yīng)用的要求,具有良好的應(yīng)用價(jià)值。本課題所取得的突破和創(chuàng)新部分有如下幾點(diǎn)：1.嚴(yán)格按照機(jī)器視覺的方法,提出了在儀表監(jiān)控識(shí)別系統(tǒng)中選用照明光源、光學(xué)鏡頭、工業(yè)相機(jī)的規(guī)則或選型指南；2.通過(guò)研究和分析Basler工業(yè)相機(jī)的視頻存儲(chǔ)格式,成功找到將YUV422格式轉(zhuǎn)換為OpenCV中使用的Mat格式的方法,奠定了使用OpenCV進(jìn)行數(shù)字圖像處理的基礎(chǔ)；3.設(shè)計(jì)出一種特征提取方法——基于相對(duì)位置、局部長(zhǎng)度、寬高比、區(qū)域面積的目標(biāo)輪廓提取方法,實(shí)現(xiàn)了感興趣區(qū)域的定位。4.在指針儀表的識(shí)別中采用了角度法來(lái)讀取指針指向位置的示數(shù),即根據(jù)指針兩端點(diǎn)坐標(biāo)的連線與水平方向的角度、表盤的最小值和最大值來(lái)識(shí)別讀數(shù)。
[Abstract]:With the development of intelligent monitoring industry and security industry at home and abroad, machine vision is more and more used in human body behavior and expression recognition PCB printed circuit detection, digital and pointer instrument recognition, product appearance detection. In many aspects, such as the classification of logistics goods, machine vision replaces artificial vision into various fields, which greatly improves the production and life efficiency of people. In the industrial field, various kinds of instruments, such as sound level meter, noise dosimeter, vibration measuring instrument, pressure gauge and so on, play an important role in production. It is easy to misread, and it is very valuable to use machine vision to identify the indication value of instrument. Based on the above situation and problems, this paper studies the application of machine vision in instrument monitoring and identification system. This paper first introduces the research significance and development status of machine vision and instrument monitoring and identification system, and then makes a detailed introduction to each component of machine vision and summarizes the method of selection. Then the hardware composition and software platform of this subject are introduced respectively. Finally, the recognition of digital and exponential instrument reading is completed by software design, and the effect of recognition is summarized. By studying the monitoring and identification of several digital and exponential instruments in industrial applications, the software design of the system is realized with the help of Microsoft's MFC OpenCVand pylon SDK development tools, and the German Basler industrial camera with excellent performance is used to obtain images. The emphasis of this subject is the algorithm design of instrument recognition. The system first uses machine vision method to collect the image of the instrument, and then uses the digital image processing technology to preprocess the image (using weighted average method for grayscale, histogram equalization for image enhancement, etc. Local adaptive binarization, morphological processing by opening and closing operation), and then extracting the value area according to the position, length, aspect ratio, contour and other appearance information on the digital meter dial. Hough transform is used to extract the circular contour and the pointer region is located. Finally, the numbers and pointers are segmented by image segmentation technique, and the characters are recognized by using the custom template matching method. The Hoff line transform detects the pointer and calculates the reading. The recognition speed and accuracy of the system can meet the requirements of application, and it has good application value. The breakthrough and innovation part of this topic has the following points: 1. In strict accordance with the method of machine vision, the rules or guidelines for selecting lighting source, optical lens and industrial camera in instrument monitoring and identification system are put forward. By studying and analyzing the video storage format of Basler industrial camera, the method of converting YUV422 format to Mat format used in OpenCV has been found successfully, which has laid the foundation of digital image processing using OpenCV. A feature extraction method based on relative position, local length, aspect ratio and area is designed. In the recognition of pointer instrument, the angle method is used to read the indication of pointer pointing position, that is, the minimum value and the maximum value of dial are recognized according to the angle between the coordinates of the two ends of the pointer and the horizontal direction.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP391.41

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本文編號(hào)：2107729