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Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04)
Recovering Dynamic Information from Static Handwritten Images
Kokubunji, Tokyo, Japan
October 26-October 29
ISBN: 0-7695-2187-8
Yu Qiao, University of Electro-Communications
Makato Yasuhara, University of Electro-Communications
This paper proposes an efficient method for recovering dynamic information from offline single-stroke hand drawing images. This method makes use of both the local analysis and global smoothness calculation. At first, a graph model is built from the skeleton. Then, odd degree nodes are resolved in a probability framework to detect the double-traced/terminal segments, and even degree nodes are analyzed by the Node Traversing Rule (NTR). We estimate the probability of two strokes being contiguous pair by PCA based angle calculation. Then, double-traced lines are identified. Finally, we calculate the smoothness for each of the possible paths by SLALOM approximation and select the smoothest one. Experiments show that our method works successfully on cursive hand drawing images.
Citation:
Yu Qiao, Makato Yasuhara, "Recovering Dynamic Information from Static Handwritten Images," iwfhr, pp.118-123, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), 2004
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