臺灣博碩士論文加值系統

隨著通訊網路的快速發展，網路上的文件已經由文字資料變成了多媒體資料，為了有效利用最少的資料與傳輸頻寬，使有限的網路頻寬可以服務更多的使用者，先進的低速率視訊壓縮技術是絕對必要的，而物件的萃取是這類演算法的關鍵技術之一。
本論文採用一利用矩量保持的原理來偵測方塊內線邊方程式的方法，運用到空間上的物件切割，首先切割影像為一群不重疊的4x4區塊，利用矩量保持原理抽取出每一區塊的線邊資訊結合區域成長法，畫面會被切割成若干均勻的區域，然後利用影像點在時間上的值的變化，本論文結合動態估測以及改變偵測的結果把前述的區域區分為移動區域及非移動區域，並聚集移動區域為前景物件，以達到物件的萃取。在萃取出視訊序列中的物件後，為了追蹤該物件於此視訊序列內的變化情形，本論文將物件的邊緣資訊經由Generalized Hough Transform( GHT )轉換成一樣版，再利用該樣版與下一張畫面內的邊緣資訊計算出物件的移動量，藉以追蹤物件的移動情形。另外，針對物件式的低速率視訊壓縮系統，本論文將矩量保持邊緣偵測方法的結果資訊，簡化為若干不同型態的樣式圖案，並根據這些樣式圖案提出一個形狀編碼及加速動態估測的方法，內容編碼部份則採用傳統DCT的方式。
實驗證明，本論文所提出之方法，可應用於物件式的低速率視訊壓縮系統，並達到提高壓縮率及加快處理速度的目的，跟傳統的方法比較，本論文所提出的方法，在不損失原本的品質下又能提昇處理的速度。

In this thesis, a new Mpeg-4-like low-bit-rate video coding based on an analytical moment-preserving edge detection technique is proposed. The first frame of each video sequence is divided into non-overlapping square blocks and coded by the mean (edge parameters) in each uniform (non-uniform) block. The coded edges are then combined with the region-growing technique to segment the image into several objects (regions) which shapes are approximated by the proposed shape-description algorithm. The segmented objects are then classified into moving and still objects according to the motion features and change differences of objects between two successive frames. The moving objects in the aggregate are called as the foreground objects of the sequence.
Based on the object templates, which are constructed by the generalized Hough transform, the objects on the successive frames are tracked by employing the detected edge patterns into the templates to compute the motion vectors of each object. The motion compensation and the texture coding are then followed to complete the design of the proposed low-bit-rate video coding method. Furthermore, by simplifying the detected edge blocks into visual patterns, a fast block-based motion estimation on the basis of visual pattern comparison is also proposed in this thesis.
Experimental results show that the proposed algorithm has acceptable performance in terms of compression quality and execution speed compared with existing methods.

項　　　目
中文摘要--------------------------------------------------i
英文摘要--------------------------------------------------ii
誌謝--------------------------------------------------iv
目錄--------------------------------------------------v
表目錄--------------------------------------------------viii
圖目錄--------------------------------------------------ix
一、緒論----------------------------------------------1
1.1背景說明------------------------------------------1
1.2研究動機------------------------------------------4
1.3研究目的------------------------------------------6
1.4論文架構------------------------------------------7
二、文獻探討------------------------------------------9
2.1MPEG-4標準----------------------------------------9
2.1.1視訊壓縮部份的標準--------------------------------10
2.2矩量保持理論之理論之相關文獻探討------------------14
2.3物件切割的相關文獻探討----------------------------18
2.4形狀描述的相關文獻探討----------------------------19
2.4.1位元圖形狀編碼------------------------------------20
2.4.2輪廓形狀編碼--------------------------------------28
2.5物件追蹤的相關文獻探討----------------------------30
三、視訊序列之物件切割、追蹤及形狀描述方法設計---------31
3.1矩量保持邊緣偵測方法設計--------------------------33
3.2結合線邊偵測及區域成長方法於空間上物件切割--------41
3.2.1利用c-mean方法進行影像量化------------------------41
3.2.2利用區域成長(region-growing)法來切割出物件--------43
3.3配合視訊序列時間上的資訊做物件切割----------------46
3.3.1動態估測法----------------------------------------47
3.3.2改變偵測法----------------------------------------51
3.3.3運用時間上的資訊協助空間上物件的切割--------------52
3.4物件追蹤------------------------------------------54
3.5物件形狀描述--------------------------------------60
四、實現一以物件為主的低速率視訊壓縮系統--------------67
4.1系統架構------------------------------------------67
4.2物件萃取部份之設計--------------------------------69
4.3物件追蹤部份之設計--------------------------------69
4.4形狀編碼部份之設計--------------------------------69
4.5動態估測及補償部份之設計--------------------------70
4.6內容編碼部份之設計--------------------------------74
五、實驗結果與分析------------------------------------79
5.1物件切割方法之實驗結果----------------------------79
5.2物件追蹤方法之實驗結果----------------------------86
5.3物件形狀描述方法之實驗結果------------------------90
5.4應用於以物件為主的低速率視訊壓縮系統--------------101
六、結論----------------------------------------------109
參考文獻--------------------------------------------------110

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