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研究生:蘇俊鴻
研究生(外文):Chun-Hung Su
論文名稱:基於機器人足球賽之模糊色彩修正及分群法之顏色分割
論文名稱(外文):Fuzzy color amendment and clustering method on color segmentation based on robot soccer game
指導教授:蔡舜宏蔡舜宏引用關係
指導教授(外文):Shun-Hung Tsai
口試委員:陳大道鄭志強蕭俊祥
口試日期:2012-07-20
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:自動化科技研究所
學門:工程學門
學類:機械工程學類
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:63
中文關鍵詞:色彩分割分群模糊分群模糊理論機器人足球
外文關鍵詞:Color SegmentationClusteringFuzzy ClusteringFuzzyRobot Soccer
相關次數:
  • 被引用被引用:1
  • 點閱點閱:186
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
由於機器人比賽時不同亮度會影響機器人視覺的判斷,因此,在本論文中,我們針對機器人足球比賽提出一個以模糊為基礎之色彩修正方法以修正在不同亮度下產生的顏色偏差。
此外,利用 Fuzzy C-means 觀念,本論文提出一個基於分群法之顏色分割方法,使得所需的顏色可以更加準確的被判斷。最後,我們利用一些例子來辨證上述所提的兩種方法能修正顏色偏差的情形,也能更有效的判斷出機器人標記的顏色。
在色彩辨識完成後,一個針對機器人足球賽的防守策略在本篇論文被提出,藉此策略降低我方機器人失分的可能性。

Since the lightness always causes the determination of the robot vision in the robot soccer game, in this thesis, we propose a fuzzy based color amendment method for the robot soccer game.
In addition, by utilizing the conception of the Fuzzy C-means, a clustering method on color segmentation is proposed for identifying colors more precious. Finally, some examples are illustrated to demonstrate the two proposed methods can amend the color deviation phenomenon and recognize the robot tag color more preciously.
After finishing the color identification, a defensive strategy for reducing the possibility of the point losses for robot soccer game is presented in this thesis.

目 錄

中文摘要 i
英文摘要 ii
誌 謝 iv
目 錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 前言 1
1.2 研究動機 2
1.3 研究目的 3
1.4 論文架構 4
第二章 文獻回顧 5
2.1 模糊理論 5
2.1.1 模糊化(Fuzzification) 6
2.1.2 模糊規則庫(Fuzzy Rule Base) 6
2.1.3 模糊推論工廠(Fuzzy Inference Engine) 7
2.1.4 解模糊化(Defuzzification) 8
2.2 色彩空間 9
2.2.1 RGB色彩空間 9
2.2.2 HSI色彩空間 10
2.2.3 HSV色彩空間 11
2.2.4 HSL色彩空間 13
2.3 分群演算法 14
2.3.1 K-means分群演算法 15
2.3.2 Fuzzy C-means分群演算法 17
第三章 Fuzzy色彩修正 21
3.1 基本構想 21
3.2 Fuzzy色彩修正方法及流程 21
3.2.1 色彩修正模糊系統設計 23
3.3色彩修正測試 27
第四章 分群法色彩分割 32
4.1 基本構想 32
4.2 機器人足球賽色塊簡介 32
4.3 K-means色彩分割方法及流程 33
4.4 K-means色彩分割測試 36
4.5 Fuzzy C-means色彩分割方法及流程 41
4.6 Fuzzy C-means色彩分割測試 42
第五章 機器人防守策略 51
5.1 競賽場地架構 51
5.2 競賽防守策略 52
5.2.1 防守策略設計 52
5.2.2 守門員防守技巧 54
5.2.3 守門員外機器人防守技巧 55
5.3 防守避障 57
第六章 結論與未來展望 59
6.1 結論 59
6.2 未來展望 59
參考文獻 61



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