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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林巍聳 | |
| dc.contributor.author | Bo-Yien Guo | en |
| dc.contributor.author | 郭柏言 | zh_TW |
| dc.date.accessioned | 2021-06-15T01:15:15Z | - |
| dc.date.available | 2012-07-30 | |
| dc.date.copyright | 2009-07-30 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-07-28 | |
| dc.identifier.citation | Adamek, T. and N. O'Connor (2003). Efficient contour-based shape representation and matching. Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval. Berkeley, California, ACM.
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'Wavelet descriptors for multiresolution recognition of handprinted characters.' Pattern Recognition 28(8): 1237-1249. Yang, H. S., S. U. Lee, et al. (1998). 'Recognition of 2D Object Contours Using Starting-Point-Independent Wavelet Coefficient Matching.' Journal of Visual Communication and Image Representation 9(2): 171-181. Zhang, D. and G. Lu (2004). 'Review of shape representation and description techniques.' Pattern Recognition 37(1): 1-19. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/42515 | - |
| dc.description.abstract | 仿射不變函數對平移、旋轉、縮放和切變等仿射轉換具有不變性，是圖形辨識的必要技術之一，「小波合成不變函數」用「合成特徵訊號」套入仿射轉換模型，因而達到保存全部輪廓資訊的目的，使圖形辨識正確率大幅提昇。「小波合成不變函數」可以分辨輪廓的細部資訊，但是也會把起始點的變動當作輪廓變異訊號，因此如何使一個輪廓對映到唯一的「小波合成不變函數」曲線就是本研究的核心課題。本論文提出「框內自然定點法」用以決定輪廓的唯一起始點，該法結合「自然軸定點」的唯一性、圖形骨架化的不變性、和區域內「最遠距離法」的準確性，本論文藉由數個實驗分析和驗證「框內自然定點法」的可用性，並且對照既有的起始點決定法，確認「框內自然定點法」在大部份情況下都可以達成決定唯一起始點的目標。 | zh_TW |
| dc.description.abstract | Affine invariant function (AIF) which is independent of affine transformations such as rotation, translation, scaling, and skewing, is a useful tool of shape recognition. Synthesized Affine Invariant Function (SAIF) which receives synthesized feature signals to determine the parametric curve features no information loss in representing the shape for recognition. While SAIF can represent the detailed contour signals, it is very sensitive to the starting point of the contour signal. By taking the advantages of the uniqueness of natural axis, the invariance of contour skeletonization, and the localization furthest centroid distance of contour, this thesis proposes the constrained natural axis method. The constrained natural axis under almost all conditions can determine a unique starting point on the contour; in turn the SAIF curve refers to the starting point is unique. That makes shape recognition based on SAIF practical and useful. Experimental results show and confirm the feasibility of the innovative method. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T01:15:15Z (GMT). No. of bitstreams: 1 ntu-98-R96921006-1.pdf: 1397989 bytes, checksum: a3496b74021fe86f31bcc2ed7f4acd7c (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | 合成仿射不變函數之起點不變性與平面圖形辨識之研究 I
誌謝 II 中文摘要 III Abstract IV 內容大綱 V 圖目錄 VIII 表目錄 X 第1章 緒論 1 1.1 研究背景 1 1.2 研究動機與貢獻 3 1.3 論文架構 4 第2章 合成仿射不變函數 5 2.1 仿射不變函數簡介 5 2.2 仿射轉換與仿射不變量 8 2.3 合成仿射不變函數 10 2.4 小波合成仿射不變函數 11 2.4.1 小波合成特徵訊號 11 2.4.2 小波合成仿射不變函數的演算式 14 2.5 餘弦合成仿射不變函數 16 2.5.1 餘弦合成特徵訊號 16 2.5.2 餘弦合成特徵訊號演算式 18 2.6 組合權重向量的類型 20 第3章：合成仿射不變函數的分析 22 3.1 分析目的 22 3.2 多重解析度分析 25 3.3 章節總結 33 第4章：起始點的不變性研究 34 4.1 起始點的影響 34 4.2 文獻回顧 35 4.3 形狀描述子 37 4.3.1 有效率的形狀描述子 38 4.3.2 形狀簽名 （Shape signature） 40 4.3.3 不變量 （invariants） 40 4.3.4 不變量簽名法 （invariant signature） 41 4.4 固定起始點法 43 4.4.1 最遠（最近）距離法（Furthest/Nearest Distance） 44 4.4.2 最大（最小）曲率法（Maximum/Minimum Curvature） 46 4.4.3 主軸定點 （Principal Axis） 50 4.4.4 自然軸定點（The Natural Axis） 52 4.5 框內自然定點法 （Skeleton Constrained Natural Axis） 54 4.5.1 自然軸定點法 （Natural Axes） 57 4.5.2 骨架定點法 （skeletonization） 58 4.5.2.1 H-M轉換 58 4.5.2.2 細化 59 4.5.3 最遠距離簽名法 （Furthest Distance） 61 第五章：實驗結果 62 5.1 實驗圖樣及分類依據 62 5.1.1 對稱性及對稱軸數目 64 5.1.2 輪廓協方差矩陣是否為常態分佈 64 5.2 測量標準 66 5.2.1 均方根誤差（Root Mean Square errors（RMS）） 66 5.2.2 相似度（Similarity rate） 66 5.3 實驗一：仿射轉換下的定點比較 68 5.3.1 實驗樣本 68 5.3.2 實驗分析 69 實驗5-1：平移均方根誤差累積直方圖 70 實驗5-2：旋轉均方根誤差累積直方圖 72 實驗5-3：縮放均方根誤差累積直方圖 74 實驗5-4：切變均方根誤差累積直方圖 76 5.3.3 歸納實驗結果 78 5.4 實驗二：仿射轉換下的辨識率 80 5.4.1 實驗樣本 80 5.4.2 實驗分析 81 5.5 實驗討論 82 第6章：結論與展望 84 6.1 研究總結 84 6.2 未來展望 85 附錄1 86 參考資料 89 | |
| dc.language.iso | zh-TW | |
| dc.subject | 仿射不變函數 | zh_TW |
| dc.subject | 小波分析 | zh_TW |
| dc.subject | 圖形辨識 | zh_TW |
| dc.subject | 框內自然定點法 | zh_TW |
| dc.subject | constrained natural axis | en |
| dc.subject | wavelet analysis | en |
| dc.subject | affine invariant function | en |
| dc.subject | Shape recognition | en |
| dc.title | 合成仿射不變函數之起點不變性與平面圖形辨識之研究 | zh_TW |
| dc.title | 2D Shape Recognition Using Synthesized Affine Invariant Function with Starting Point Invariance | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 鍾鴻源,許新添,邱榮輝 | |
| dc.subject.keyword | 圖形辨識,仿射不變函數,框內自然定點法,小波分析, | zh_TW |
| dc.subject.keyword | Shape recognition,affine invariant function,constrained natural axis,wavelet analysis, | en |
| dc.relation.page | 91 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-07-28 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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