本文選題：圖像處理 + 馬賽克　； 參考：《廣東工業(yè)大學(xué)》2017年碩士論文

【摘要】：馬賽克作為一種常用在露面墻壁、地板外觀等方面的裝飾品,以其艷麗明亮的風(fēng)格,在裝飾領(lǐng)域受到越來(lái)越多人的青睞。然而現(xiàn)階段馬賽克分揀工藝大量依靠人工,勞動(dòng)成本投入大效率低,另有一部分分揀工藝采用傳統(tǒng)傳感器組合檢測(cè)方法,來(lái)識(shí)別檢測(cè)分揀目標(biāo),雖然一定程度上能提高分揀系統(tǒng)的自動(dòng)化性能,但無(wú)法滿(mǎn)足馬賽克缺陷檢測(cè)要求,隨著計(jì)算機(jī)圖形技術(shù)的發(fā)展,采用相機(jī)來(lái)代替人眼的機(jī)器視覺(jué)技術(shù)越來(lái)越成熟,其具有可視化、無(wú)損、實(shí)時(shí)、通用性強(qiáng)等特點(diǎn),應(yīng)用在馬賽克分揀領(lǐng)域,彌補(bǔ)了人工與傳感器組合檢測(cè)性能的不足。本文在查閱大量相關(guān)領(lǐng)域文獻(xiàn)資料的基礎(chǔ)上,基于機(jī)器視覺(jué)知識(shí)展開(kāi)了對(duì)馬賽克目標(biāo)的分揀技術(shù)研究,過(guò)程中提出了一整套視覺(jué)識(shí)別與檢測(cè)方案,并搭建實(shí)驗(yàn)平臺(tái),對(duì)研究對(duì)象進(jìn)行了識(shí)別與缺陷檢測(cè)實(shí)驗(yàn)。本文的主要內(nèi)容包括以下幾個(gè)方面:1)從馬賽克識(shí)別與分揀工藝出發(fā),設(shè)計(jì)系統(tǒng)方案,搭建實(shí)驗(yàn)硬件與控制平臺(tái),根據(jù)系統(tǒng)所處的實(shí)驗(yàn)環(huán)境,分析計(jì)算各單元零部件參數(shù)要求,選擇合適型號(hào)的產(chǎn)品。2)提出了一整套包含圖像灰度處理、圖像濾波、圖像形態(tài)學(xué)處理、圖像分割等一系列圖像處理技術(shù)的視覺(jué)識(shí)別方案,基于此視覺(jué)識(shí)別方案提取馬賽克目標(biāo)輪廓與表面灰度直方圖特征,依據(jù)圖像特征分別采用輪廓匹配與灰度值匹配來(lái)識(shí)別圖像中馬賽克目標(biāo)與檢測(cè)缺陷。3)提出了一種基于運(yùn)動(dòng)距離來(lái)觸發(fā)相機(jī)的取圖模型,根據(jù)傳送帶移動(dòng)距離、相機(jī)視野范圍、目標(biāo)尺寸三者來(lái)計(jì)算相機(jī)觸發(fā)節(jié)點(diǎn),達(dá)到對(duì)移動(dòng)傳送帶上的目標(biāo)物體不遺漏且盡量少重復(fù)取圖的目的。4)通過(guò)基于機(jī)器人的相機(jī)內(nèi)外參標(biāo)定,求解相機(jī)像素坐標(biāo)系到機(jī)器人坐標(biāo)系之間的轉(zhuǎn)換矩陣,再結(jié)合傳送帶編碼器反饋的位置數(shù)據(jù),實(shí)現(xiàn)對(duì)傳送帶上的目標(biāo)實(shí)時(shí)跟蹤與抓取任務(wù)。本文采用機(jī)器視覺(jué)技術(shù)來(lái)對(duì)馬賽克目標(biāo)進(jìn)行識(shí)別分揀,經(jīng)多次反復(fù)實(shí)驗(yàn)證明該馬賽克分揀系統(tǒng)具有準(zhǔn)確率高、實(shí)時(shí)性強(qiáng)和速度快等優(yōu)點(diǎn),且具備良好的可擴(kuò)展性能,能應(yīng)用于其他具有明顯特征的非馬賽克產(chǎn)品的識(shí)別與分揀任務(wù)。
[Abstract]:Mosaic as a common decoration in the appearance of walls, floors and other aspects, with its brilliant and bright style, in the decoration field by more and more people's favor. However, at the present stage, the mosaic sorting process relies heavily on labor, and the labor cost is large and inefficient. Another part of the sorting process uses the traditional sensor combination detection method to identify the sorting targets. Although the automatic performance of sorting system can be improved to some extent, it can not meet the requirements of mosaic defect detection. With the development of computer graphics technology, the machine vision technology that uses camera to replace human eyes becomes more and more mature. It has the characteristics of visualization, nondestructive, real-time and versatility. It is used in the mosaic sorting field and makes up for the deficiency of the performance of the combination of artificial and sensor. On the basis of consulting a lot of literature in related fields, this paper studies the sorting technology of mosaic target based on machine vision knowledge, and puts forward a set of vision recognition and detection scheme, and builds an experimental platform. Experiments on identification and defect detection were carried out. The main contents of this paper include the following aspects: 1) from the mosaic identification and sorting technology, design the system scheme, build the experimental hardware and control platform, according to the experimental environment, analyze and calculate the parameters of each unit. (2) A whole set of visual recognition schemes including image grayscale processing, image filtering, image morphology processing, image segmentation and so on are proposed. Based on this vision recognition scheme, the feature of mosaic target contour and surface gray histogram is extracted. According to the image features, the mosaic target in the image is identified by contour matching and gray value matching. (3) A model based on moving distance to trigger the camera is proposed. According to the moving distance of the conveyor belt, the range of the camera field of vision is obtained. The target size is used to calculate the camera trigger node, so that the target object on the moving conveyor belt is not omitted and the image is retrieved as little as possible.) the camera is calibrated based on the robot's internal and external parameters. The transformation matrix between camera pixel coordinate system and robot coordinate system is solved, and the real-time tracking and grasping task of the target on the conveyor belt is realized by combining the position data feedback from the conveyor belt encoder. In this paper, the machine vision technology is used to identify and sort the mosaic target. It is proved by repeated experiments that the mosaic sorting system has the advantages of high accuracy, high real-time and high speed, and has good expansibility. It can be used in the identification and sorting of other non-mosaic products with obvious characteristics.
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 胥磊;;機(jī)器視覺(jué)技術(shù)的發(fā)展現(xiàn)狀與展望[J];設(shè)備管理與維修;2016年09期

2 卞正崗;;機(jī)器視覺(jué)技術(shù)的發(fā)展[J];中國(guó)儀器儀表;2015年06期

3 石煒;邵珠慶;李巍巍;;機(jī)器視覺(jué)在圓錐滾子軸承內(nèi)圈外表面缺陷檢測(cè)中的應(yīng)用[J];機(jī)械設(shè)計(jì)與制造;2015年05期

4 謝森林;曾輝;董曉慶;;基于機(jī)器視覺(jué)的日用瓷表面缺陷檢測(cè)[J];韓山師范學(xué)院學(xué)報(bào);2014年06期

5 王永翔;吳志鵬;黎勉;;藝術(shù)馬賽克自動(dòng)排版生產(chǎn)線(xiàn)設(shè)計(jì)[J];機(jī)床與液壓;2014年20期

6 雷敏華;陳良;;基于機(jī)器視覺(jué)的端子尺寸檢測(cè)系統(tǒng)[J];機(jī)電工程技術(shù);2013年07期

7 宮赤坤;藍(lán)黎恩;;基于運(yùn)動(dòng)學(xué)的Delta機(jī)器人優(yōu)化設(shè)計(jì)[J];現(xiàn)代制造工程;2013年05期

8 何春華;張雪飛;胡迎春;;基于改進(jìn)Sobel算子的邊緣檢測(cè)算法的研究[J];光學(xué)技術(shù);2012年03期

9 艾青林;黃偉鋒;張洪濤;張立彬;;并聯(lián)機(jī)器人剛度與靜力學(xué)研究現(xiàn)狀與進(jìn)展[J];力學(xué)進(jìn)展;2012年05期

10 賈慶蓮;王春霞;;連續(xù)變焦鏡頭焦距輸出結(jié)構(gòu)的設(shè)計(jì)[J];中國(guó)光學(xué)與應(yīng)用光學(xué);2010年06期

，

本文編號(hào)：2057350