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農(nóng)業(yè)機(jī)械學(xué)研究生論文開題報(bào)告(2)

時(shí)間:2024-08-03 08:07:54 學(xué)人智庫(kù) 我要投稿
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農(nóng)業(yè)機(jī)械學(xué)研究生論文開題報(bào)告(2)

  第4章紅棗缺陷檢測(cè)40-45

農(nóng)業(yè)機(jī)械學(xué)研究生論文開題報(bào)告(2)

  4.1紅棗圖像的采集40-41

  4.2紅棗圖像的處理41-42

  4.3紅棗圖像缺陷的分割42-43

  4.4缺陷有無(wú)的判別43-44

  4.4.1確定判斷依據(jù)43

  4.4.2判斷結(jié)果43-44

  4.5小結(jié)44-45

  第5章紅棗紋理檢測(cè)45-53

  5.1紋理特征的提取45-47

  5.1.1基于統(tǒng)計(jì)分析的紋理識(shí)別方法研究45-47

  5.2材料與方法47-48

  5.3紅棗圖片采集48

  5.4紅棗圖像預(yù)處理48

  5.5BP人工神經(jīng)網(wǎng)絡(luò)顏色分級(jí)48-50

  5.5.1BP神經(jīng)網(wǎng)絡(luò)簡(jiǎn)介48-49

  5.5.2BP神經(jīng)網(wǎng)絡(luò)的訓(xùn)練學(xué)習(xí)49-50

  5.6BP神經(jīng)網(wǎng)絡(luò)的紅棗紋理分級(jí)50-51

  5.7紋理與水分試驗(yàn)51-52

  5.8小結(jié)52-53

  第6章紅棗顏色檢測(cè)53-61

  6.1顏色模型的確定53-55

  6.1.1RGB顏色模型54

  6.1.2HSI顏色模型54-55

  6.1.3顏色模型轉(zhuǎn)換55

  6.2顏色特征的提取55-57

  6.2.1紅棗圖像采集56

  6.2.2紅棗圖像背景分割56

  6.2.3特征提取56-57

  6.3RGB模型和HSI模型的紅棗顏色分級(jí)57-59

  6.3.1實(shí)驗(yàn)材料與方法57-58

  6.3.2輸入層設(shè)計(jì)58

  6.3.3輸出層設(shè)計(jì)58

  6.3.4中間層設(shè)計(jì)與網(wǎng)絡(luò)訓(xùn)練58

  6.3.5分級(jí)結(jié)果58-59

  6.4糖度與顏色的關(guān)系59-60

  6.5小結(jié)60-61

  第7章結(jié)論與展望61-63

  7.1結(jié)論61-62

  7.2展望62-63

  附錄63-70

  參考文獻(xiàn)70-75

  致謝75-76

  六、目前已經(jīng)閱讀的主要文獻(xiàn)

  [1]張冬.基于機(jī)器視覺的紅棗分級(jí)檢測(cè)技術(shù)研究[D].寧夏大學(xué),2008.

  [2]賈文婷等.新疆南疆地區(qū)紅棗產(chǎn)業(yè)營(yíng)銷現(xiàn)狀與戰(zhàn)略思考金新文[J].新疆農(nóng)墾經(jīng)濟(jì),2014,01:37-39.

  [3]周健華.紅棗分級(jí)機(jī)的設(shè)計(jì)及試驗(yàn)研究[D].新疆農(nóng)業(yè)大學(xué),2012.

  [4]龐江偉,應(yīng)義斌.機(jī)器視覺在水果缺陷檢測(cè)中的研究現(xiàn)狀[J].農(nóng)機(jī)化研究,2006,09:47-49.

  [5]趙曉霞.計(jì)算機(jī)視覺技術(shù)在農(nóng)業(yè)中的應(yīng)用[J].科技情報(bào)開發(fā)與經(jīng)濟(jì),2004,04:124-126.

  [6]Pathare,P.B.,Opara,U.L.,&Al-Said,F.A.(2013).Colourmeasurementandanalysisinfreshandprocessedfoods:Areview.FoodandBioprocessTechnology,6(1),36–60.

  [7]Wu,D.,&Sun,D.W.(2013).Colourmeasurementsbycomputervisionforfoodqualitycontrol—Areview.TrendsinFoodScience&Technology,29(1),5–20.

  [8]Zheng,C.X.,Sun,D.W.,&Zheng,L.Y.(2006).Recentdevelopmentsandapplicationsofimagefeaturesforfoodqualityevaluationandinspection—Areview.TrendsinmFoodScience&Technology,17(12),642–655.

  [9]Leemans,V.,Magein,H.,&Destain,M.F.(2002).On-linefruitgradingaccordingtotheirexternalqualityusingmachinevision.BiosystemsEngineering,83(4),397–404.

  [10]Kurita,M.(2006).Extractionmethodsofcolorandshapefeaturesfortomatograding.ShokubutsuKankyoKogaku,18(2),145–153.

  [11]Blasco,J.,Aleixos,N.,Gomez-Sanchis,J.,&Molto,E.(2009).Recognitionandclassificationofexternalskindamageincitrusfruitsusingmultispectraldataandmorphologicalfeatures.BiosystemsEngineering,103(2),137–145.

  [12]Blasco,J.,Cubero,S.,Gomez-Sanchis,J.,Mira,P.,&Molto,E.(2009).Developmentofamachinefortheautomaticsortingofpomegranate(Punicagranatum)arilsbasedoncomputervision.JournalofFoodEngineering,90(1),27–34.

  [13]Cubero,S.,Aleixos,N.,Molto,E.,Gomez-Sanchis,J.,&Blasco,J.(2011).Advancesinmachinevisionapplicationsforautomaticinspectionandqualityevaluationoffruitsandvegetables(vol4,pg487,2011).FoodandBioprocessTechnology,4(5),829–830.

  [14]Zou,X.B.,Zhao,J.W.,&Li,Y.X.(2007).Applecolorgradingbasedonorganizationfeatureparameters.PatternRecognitionLetters,28(15),2046–2053.

  [15]Mendoza,F.,Dejmek,P.,&Aguilera,J.M.(2006).Calibratedcolormeasurementsofagriculturalfoodsusingimageanalysis.PostharvestBiologyandTechnology,41(3),285–295.

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