本論文提出一新的色情影像偵測法，本論文的貢獻可分為二個面向，其一為提出一新的膚色偵測演算法，此法乃植基於非監督式的Mean-Shift分群法，能可靠且有效地偵測出膚色區域，不易受環境光源變化所影響；另一貢獻為提出一多層次驗證的色情影像判別法，此法能在維持高偵測率的前提下，有效地將為偽陽性錯誤降至極低。實驗結果顯示，本論文所提方法具有極佳的運作效能。

This thesis proposes a new pornography detection, the contribution divided into two parts. On the one hand proposes a new skin detection algorithm, the method is unsupervised-based Mean-Shift clustering, can be reliable and effective to detect skin regions, is not easy affected environment illuminant change. On the other hand proposes a multilayer verification pornography distinguish method, this method on the premise that maintain high detection ratio, effectively false positive drops to extremely lowly. The experiment results show, this paper proposes method with perfect performance.

【摘要】 i
【Abstract】 ii
【誌謝】 iii
【目錄】 iv
【表目錄】 v
【圖目錄】 vi
第一章 序論 1
1-1 動機與目的 1
1-2 文獻探討 2
1-3 系統架構 7
1-4 論文架構 9
第二章 本體論 11
2-1 本體論定義 11
2-2 系統架構與方法流程 12
第三章 研究方法 15
3-1 以Mean-Shift為基礎的膚色偵測演算法 16
3-2 初步膚色判斷 19
3-3 膚色區域確認 27
3-4 紋理分析 32
3-5 色情偵測 36
第四章 實驗結果 46
4-1 實驗平台 46
4-2 實驗一 47
4-3 實驗二 48
4-4 實驗三 50
4-5 實驗四 51
4-6 實驗五 52
4-7 實驗六 54
4-8 實驗七 57
第五章 結論與未來展望 62
5-1 結論 62
5-2 未來展望 63
【參考文獻】 64

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