臺灣博碩士論文加值系統

影像分割(Image segmentation)在電腦視覺(Computer vision)及圖形識別(Pattern recognition)領域中扮演一個相當重要的角色。而在許多的影像分割方法中，決定閥值(Thresholding)是一個常用且有效的分割方法。在許多決定閥值方法中，以輸入、輸出影像之動量維持守恆之原理來決定閥值(Moment Preserving Thresholding Method)是一個為人所熟悉、快速且簡單的決定閥值方法。本論文針對此動量守恆決定閥值方法作改進，利用此守恆方法所計算出來的群組比率值及群組灰階代表值，進一步以等腰三角形來模擬近似輸入影像之灰階分佈圖的山峰形狀，然後以此山峰位置來決定所需的閥值。本論文對不同灰階影像作二階及三階決定閥值之試驗，實驗結果證明所提方法之可行及有效性。

Thresholding is frequently used for image segmentation. One of the most popular approach to thresholding is the moment-preserving thresholding method proposed by Tsai in 1985. However, it does not work well when the peaks of a histogram have a great size variation. Hence in this study we propose a simple and effective improvement in Tsai’s method such that suitable thresholds can be found even when the histogram has peaks with a great size variation. In the proposed method, the fractions of below-threshold and above-threshold pixels and their represented gray values are first computed by Tsai’s moment-preserving thresholding method. They are next used to simulate shapes of peaks in the histogram of the input image. Then the thresholds are determined based on the locations of the simulated peaks. Experimental results show the effectiveness of the proposed improvement.

目 錄
中文摘要…………………………………………………………………i
致謝 …………………………………………………………………ii
目錄 …………………………………………………………………iii
圖目錄 …………………………………………………………………iv
表目錄 …………………………………………………………………vi

第一章　緒言……………………………………………………………1
第二章　利用動量守恆原理決定閥值…………………………………4
　　2.1 簡介動量守恆決定閥值方法………………………4
　　2.2 本論文所提改進方法………………………………7
第三章　實驗結果………………………………………………………12
第四章　結論……………………………………………………………25
參考文獻…………………………………………………………………26

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