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研究生:李宗雄
研究生(外文):Tsung-Hsiung Li
論文名稱:結合區塊匹配及Viterbi演算法之影像追蹤系統
論文名稱(外文):Block Matching and Viterbi Algorithm for Image Tracking
指導教授:鄭木火
指導教授(外文):Mu-Huo Cheng
學位類別:碩士
校院名稱:國立交通大學
系所名稱:電機與控制工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
中文關鍵詞:影像追蹤影光流區塊匹配演算法馬可夫鏈Viterbi演算法
外文關鍵詞:Image TrackingOptical flowBlock Matching AlgorithmMarkov ChainsViterbi Algorithm
相關次數:
  • 被引用被引用:2
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  • 下載下載:73
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影像追蹤的應用範圍很廣泛,舉凡機器視覺、自動監控系統、交通流量警報系統等等。對於影像追蹤系統而言,物體運動估測的準確度直接影響整個系統的效能。然而在真實的環境中,若採用區塊匹配演算法來估測物體的運動,其準確度容易受到雜訊的影響。因此在本論文中提出了結合區塊匹配演算法及Viterbi演算法的影像追蹤系統。首先,利用區塊匹配演算法計算影像之間的影光流速度,接下來從影光流速度的分佈中估測馬可夫鏈模組參數,最後利用Viterbi演算法估測影像追蹤系統的物體運動。
經由實驗模擬驗證,結合區塊匹配及Viterbi演算法確實能夠改善影像追蹤系統的抗雜訊能力。
An image tracking system has many
applications for machine vision, auto-surveillance system, and
traffic flow alarm system. In the image tracking system, the
performance depends mostly on the precision of motion estimation.
The precision of motion estimation using block matching algorithm,
however, is highly sensitive to noise in the real environment. In
this thesis, we present a block matching and Viterbi algorithm for
image tracking. First, the block matching algorithm is used to
compute the optical flow between image frames . Then the model
parameters of Markov chain are estimated using the distribution
of optical flow. Finally, Viterbi algorithm is employed to
estimate the motion by which the image tracking system is
developed. Experimental results demonstrate that the noise
immunity of the image tracking system is improved.
第一章、 緒論
第一節、研究動機
第二節、文獻回顧
第三節、論文架構
第二章、運動估測
第一節、影光流
第二節、Horn與Schunck提出的演算法
第三節、區塊匹配演算法
第三章、影像追蹤系統
第一節、系統架構
第二節、離散時間馬可夫鏈
第三節、Viterbi演算法
第四節、運動方向估測
第五節、運動距離估測
第六節、Viterbi演算法實例
第四章、影像追蹤系統之PI控制器設計
第一節、羅斯-赫維茲穩定準則
第二節、PI控制器設計
第五章、實驗與模擬結果
第一節、訊號雜訊比(SNR)
第二節、實驗與模擬結果
第六章、結論
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