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標題: 利用鏈碼方向性抽取平面物件特徵以達成形狀辨識及分類的方法
Planar Shape Recognition and Classification Based Chain-Codes Direction Function
作者: 戴紹國
Dai, S.K.
關鍵字: shape recognition
shape classification
critical point detection
direction flow change
出版社: 應用數學系
摘要: 在這篇論文中,我們提出了一種相當特殊,且具有高效率的方法,利用輪 廓的鏈碼所具有的方向性來計算弧線段曲度的估計值,進而決定一個物件 輪廓上的臨界點。然後求出以每個臨界點為頂點的弧線段的角度,來做為 這個物件的特徵,再使用修改過的WLD來計算物件之間的距離,以求取其相 似的程度並將物件加以分類。經過修改後的WLD具有比對模糊性,能夠對雜 訊有更高的容忍度,進而使物件之形狀辨識及分類更具彈性。
In this paper, an approach to shape recognition/ classification based on Di-rection Flow Change (DFC) function and extended WLD method is presented. The DFC function is able to locate a set of critical points for a shape. A sequence of angles corresponding to these critical points can be computed to serve as the major features of a shape image. The extended WLD method measures the distance between two arbitary shapes whose representation are sequences ofangles. Using DFC function to find critical points is very efficient. Shaperecognition/ classification becomes very flexible of the extended WLD methodis both effective and robust for planar shape recognition/ classification.
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