評価関数の差分化による視覚的曲線の高速検出法
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概要
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Human visual sensation has an ability finding a continuous curve from a noisy binary image. In the previous paper, we have proposed a high-precision method to detect perceptive curves from a binary image. Pre-reported method generates a graph that is accumulated evaluation values of appropriate partial curves. Then a perceptive curve is detected by global edge tracing from the graph. This method has a problem that partial curve searching requires long times. To solve this problem, an evaluation function employed in this method is deformed into a recurrence relation. Then we exhibit that Dynamic Programming can be applied to a partial curve searching algorithm. Moreover by ordering a searching-priority in the searching, calculation costs can be reduced without an additional parameter and an accuracy deterioration. Experimental results show that a processing speed of proposed method is 165 times faster than pre-reported method as the average. It is also shown that proposed method is faster than conventional methods.