基於影像內容(Content-Aware)的影像尺寸調整技術(Image Retargeting)，有別於傳統方法，基於影像的內容計算其重要性的區塊(Region-of-Interest, ROI)，能在影像長寬比率的改變後，將整個重要性區塊於影像中保留原比例而非因擠壓使變形。
本論文提出一種基於影像切縫(Seam Carving)的調整方法，結合影像梯度(Gradient)測量、HSV色彩空間、皮膚偵測方法計算顯著性影像(Saliency Map)，並作為影像尺寸調整的依據。於迭代(Iteration)過程中使用小波轉換(Wavelet Decompose)分析，小波係數變異的幅度等同於影像結構破壞的程度，以此關聯變換使用均勻性縮放方法，以門檻值限制資訊遺失的程度。
本論文的實驗設計對影像的調整極限比較及使用性評估來證明提出之方法，於特定影像種類更能簡單和有效地，基於影像內容調適影像於特定長寬比，也維持影像原有的品質。

Content-Aware Image Retargeting, differ from the traditional resize method which recognition of the Region-of-Interest(ROI) based on Content-Aware. After change the aspect ratio while preserving visually prominent whole regions rather than distributes the distortion.
In this article, we will propose a resize method that is based on the Seam Carving. The method base on an Saliency Map that combine the result of color gradient and HSV color space and skin detection to determine visual importance of pixels. Using the wavelet coefficient range of variation with a threshold to avoid seriously artifacts, and switch the resizing method from our method to scaling for preventing the shape distortion.
In our experiment show the image retargeting result with limitation, and analysis the practical feasibility to prove our method preserves the important contents better than existing methods.

摘 要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 VIII
第1章 導論 1
1.1 前言 1
1.2 研究目的 2
1.3 研究架構 4
第2章 文獻探討 6
2.1 基於裁切方法(Cropping Based Methods) 6
2.2 基於變形方法(Warping Based Methods) 8
2.3 基於Seam Carving方法 10
2.3.1 單一運算(Single-Operator) 13
2.3.2 多種運算(Multi-Operator) 13
第3章 動態影像尺寸調整技術 15
3.1 顏色變異程度 16
3.1.1 Sobel Filter 16
3.1.2 HSV 17
3.1.3 加強權重(Balance Map) 18
3.2 膚色過濾 19
3.3 小波轉換 21
3.3.1 水平分割 22
3.3.2 垂直分割 23
3.3.3 調整極限 24
第4章 實驗設計與結果 26
4.1 實驗設計 26
4.2 實驗影像結果比較 26
4.2.1 實驗影像來源 27
4.2.2 實驗結果 28
4.2.3 小結 29
4.3 使用性評估 30
4.3.1 開發環境 30
4.3.2 實驗流程 31
4.3.3 系統架構 32
4.3.4 受測者影像結果比較 33
4.4 小結 48
第5章 結論與未來研究方向 49
Reference 50
附錄 52

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