發(fā)布時間：2018-07-08 14:26

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

【摘要】：隨著國內(nèi)外智能監(jiān)控行業(yè)和安防產(chǎn)業(yè)的發(fā)展,機器視覺越來越多地應用在人體行為及表情識別、PCB印刷電路檢測、數(shù)字和指針儀表識別、產(chǎn)品外觀檢測、物流物品分類等諸多方面,機器視覺取代人工視覺進入各種領(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,各類儀表如聲級計、噪聲劑量計、震動測量儀、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,利用機器視覺來識別儀表示值非常有應用價值�；�于上述形勢和問題,本論文研究了機器視覺在儀表監(jiān)控識別系統(tǒng)中的應用。論文首先介紹了機器視覺和儀表監(jiān)控識別系統(tǒng)的研究意義和發(fā)展現(xiàn)狀,接著對機器視覺各個組成部分做了詳細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,最后通過軟件設計完成了對數(shù)字和指針式儀表識別的讀數(shù)識別,并對識別的效果做了總結(jié)。通過研究工業(yè)應用中的幾種數(shù)字式和指針式儀表的監(jiān)控識別,本課題采用了具有優(yōu)質(zhì)性能的德國Basler工業(yè)攝像頭獲取圖像,借助于微軟的MFC、OpenCV、 pylon SDK開發(fā)工具實現(xiàn)系統(tǒng)的軟件設計。其中本課題的重點是儀表識別的算法設計。系統(tǒng)首先使用機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)對圖像進行預處理操作(使用加權(quán)平均法進行灰度化、使用直方圖均衡化進行圖像增強、進行局部自適應二值化、用開閉操作進行形態(tài)學處理)；進而根據(jù)數(shù)字儀表表盤上的位置、長度、寬高比、輪廓等外觀特征信息提取示值區(qū)域,對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)字和指針分割出來,采用自定義模板匹配方法識別出字符、霍夫線變換檢測出指針并計算讀數(shù)。通過實際場景下的測試,本系統(tǒng)的識別速度和識別準確度均能夠達到應用的要求,具有良好的應用價值。本課題所取得的突破和創(chuàng)新部分有如下幾點：1.嚴格按照機器視覺的方法,提出了在儀表監(jiān)控識別系統(tǒng)中選用照明光源、光學鏡頭、工業(yè)相機的規(guī)則或選型指南；2.通過研究和分析Basler工業(yè)相機的視頻存儲格式,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進行數(shù)字圖像處理的基礎；3.設計出一種特征提取方法——基于相對位置、局部長度、寬高比、區(qū)域面積的目標輪廓提取方法,實現(xiàn)了感興趣區(qū)域的定位。4.在指針儀表的識別中采用了角度法來讀取指針指向位置的示數(shù),即根據(jù)指針兩端點坐標的連線與水平方向的角度、表盤的最小值和最大值來識別讀數(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.
【學位授予單位】：山東大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TP391.41

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本文編號：2107729