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研究生:廖耿毅
研究生(外文):Keng-Yi Liao
論文名稱:應用機器視覺於建構木紋掃描與木材缺陷檢測系統
論文名稱(外文):Automated Inspection of Application to the Construction of Wood Grain Scanning and Wood Surface Defect Inspection Systems
指導教授:田方治田方治引用關係
口試委員:徐亞琛陳協慶
口試日期:2012-07-18
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:工業工程與管理系碩士班
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:79
中文關鍵詞:電腦視覺檢測木材缺陷木材掃描影像縫合支持向量機
外文關鍵詞:Computer Visual Inspectionwood defectswood scanningImage StitchingSupport Vector Machine
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木材因為取得容易,廣泛應用於日常用品中。木材的好壞主要由樹木的品種和缺陷所決定,而樹木容易受到季節、氣候、生物和生長環境等因素而產生缺陷,主要可分為三個部分:天然缺陷,如木節、斜紋理以及因生長應力或自然損傷而形成的缺陷;生物為害的缺陷,主要有腐朽、變色和蟲蛀等因素;另外,乾燥及機械加工引起的缺陷也是引起木材缺陷的主要原因之一。木材缺陷檢測通常是利用人眼檢視,人眼檢視常因個人主觀或內外在環境而影響檢測結果。
本研究之目的在開發自動化木紋掃描與檢測系統,並利用支持向量機於木節良莠分類上。於系統上主要可分為兩部分:木材輸送帶系統(Wood Conveying System)和木材缺陷檢測系統(Wood defect inspection system)。木材輸送系統主要的功能是使木材在檢測和輸送的流程中能順利進行,透過感應器與譯碼器的控制使工業相機能夠順利取像;木材缺陷檢測系統則透過電腦視覺將取得之部份影像,運用影像縫合技術將數張影像縫合成木材完整影像,並藉由影像處理之技術取得缺陷之型態位置與大小,作為後製程切割參考之依據。在木節分類上,因本身有良莠之區分,故以支持向量機分類木節之好壞。


Wood is easy to get and also widely used in our daily lives. The quality of the wood depends on the tree species and its defects. Trees may be damaged because of many causes such as season, climate, biology and environment. Wood defects can be divided into three categories: natural defects such as knots, grain, or caused by the stress of developing new xylem or natural damage; biological defects such as rot, discoloration, and decay by insects and so on. Besides, defects caused by arid and machine are another factors resulting in the defects. Currently, wood defect inspection is usually conducted by human eyes, but their inspection results are seriously subject to personal subjective view, the internal, and external environmental factors.
Therefore, the purpose of this study is to develop an effective wood scanning system and a precise inspection system, using Support Vector Machines for the classification of the knots. The content of this project can be divided into two parts: wood conveying and wood defect inspection systems. The main function of wood conveying system is to make wood testing and delivery process proceed smoothly; the industrial camera is controlled by the sensor and the encoder for the image capture. After getting the wood images, the system combines those images into a complete image of wood by the stitching techniques. Thus, the system applies image process to wood characteristics and its defect analysis as the base for cutting. As for the classification of knots, with the distinction between good and bad, Support Vector Machines are used for the classification.


摘 要 i
致 謝 iv
目 錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究範圍與限制 2
1.4 研究架構 4
第二章 文獻探討 6
2.1 自動化視覺檢測之概論 6
2.2影像縫合 10
2.2.1影像比對 11
2.2.2 影像拼接與融合 12
2.3 表面缺陷檢驗與方法 12
2.3.1木材表面之缺陷 13
2.3.2缺陷檢測方法於木材上 15
2.4 支持向量機 18
2.4.1 核函數特徵空間 22
2.4.2支持向量機之應用 23
第三章 研究方法 25
3.1 研究方法概述 25
3.2 木紋掃描與木材缺陷之影像處理 30
3.2.1 基於影像縫合於木材 31
3.3木材表面缺陷檢測 34
3.3.1影像分割於木材 34
3.3.1.1影像門檻化 34
3.3.1.2 邊緣檢測 35
3.3.2影像強化於木材缺陷 37
3.3.2.1 侵蝕於木材影像 37
3.3.2.2 封閉算子於木材影像 38
3.3.2影像缺陷偵測與分析於木材缺陷 40
3.4應用SVM於木材缺陷分類 42
3.4.1 效能驗證 44
第四章 實驗結果與分析 45
4.1 木材檢測系統硬體之建構 45
4.1.1 木材輸送帶系統 45
4.1.2 木材光罩檢測系統 46
4.2 影像縫合之木材實驗結果 51
4.3木材缺陷分析實驗結果 55
4.3.1 木材缺陷實驗流程 55
4.3.2 木材本體之影像分割 57
4.3.3 木材檢測方法參數設定與影像缺陷檢測 59
4.3.4 實驗數據分析與討論 62
第五章 結論與未來研究方向 64
5.1 結論 64
5.2 研究貢獻 65
5.3 未來研究方向 65
參考文獻 67
附錄A 木材瑕疵樣本數據 70
附錄B 交叉驗證之參數數據 73
附錄C 影像縫合之測試數據 78


中文部分
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英文部份
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