臺灣博碩士論文加值系統

影像是用來辨識成人網站最重要的資訊，以往的影像辨識技術只注重單一影像的辨識率，但是色情影像通常是以群組的方式出現，而非單一影像，因此本論文改採影像群組辨識的觀念，以提高辦識的準確率。
色情影像群組的辨識率取決於單一色情影像的辨識率和最後的決策法則，以前辨識色情影像群組的方法沒有考慮如何調整單一色情影像的辨識率，而只有提出決策法則，我們的研究顯示這種方式會造成不規則的ROC辨識曲線圖，因而不利於系統辨識率的調校。
本論文提出的方法同時考量單一色情影像辨識率的調校和決策法則的參數設定這兩項因素，最終目的是要達成影像群組的最佳辨識率，而不是單一影像的最佳辨識率。
我們的方法是利用機率理論，計算在不同參數的條件下對於影像群組所能達成的辨識率，然後根據計算結果挑選出最佳的參數設定，並將它們記錄在一個參考表格中。當要辨識一個未知的影像群組時，使用者可以先設定想要達到的辨識率，系統便會從參考表格中取得適當的參數設定，再用該組參數對未知的影像群組進行辨識。實驗結果顯示和以前的方法相較之下，本論文提出的方法對於影像群組能夠達到更高的辨識率。

The recognition accuracy of adult image groups depends on the performance of the adult image recognizer and the final decision rule. Earlier methods of recognizing adult image groups do not take into account the performance tuning of the adult image recognizer but only focus on the decision rule. Our study shows that this may lead to an irregular ROC curve which is unfavorable for system performance adjustment.
The proposed method considers the two factors together and aims at achieving optimal recognition accuracy for image groups but not for individual images. Our method resolves an optimal parameter lookup table by means of calculating the probability of correctly classifying image groups for different parameter settings. To classify an unknown image group, the desired recognition accuracy can be specified first and the suitable parameters are retrieved from the lookup table to initialize the image recognizer for scanning the image group. Experimental results show that the proposed method can attain higher recognition accuracy than the earlier methods.

誌謝 I
摘要 II
Abstract III
目錄 IV
圖目錄 VI
表目錄 VII
第一章 緒論 1
1.1 研究動機及背景 1
1.2 研究方法和貢獻 2
1.3 論文架構 2
第二章 文獻探討 4
2.1 單張色情影像辨識 4
2.2 色情影像群組辨識 5
2.3 類神經網路 6
2.3.1 類神經網路簡介 6
2.3.2 類神經神經元模型 7
2.3.3 類神經網路模型 9
2.3.4 應用類神經網路於影像辨識相關研究 12
2.4 組合與條件機率 15
2.5 ROC曲線 16
第三章 色情影像群組辨識 17
3.1 辨識色情影像群組的理論探討 17
3.2 提出的色情影像群組辨識方法 21
第四章 系統實作 27
4.1 單張色情影像辨識 27
4.2 色情影像群組辨識 31
第五章 實驗結果 34
第六章 結論與未來展望 38
參考文獻 39

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