【摘要】 描述了一种通用的在复杂特征图像中检测主曲线的新算法.基于曲线最短路径和方向偏移判据,主曲线检测的所有运算都在图形表达中进行.在图形网络搜寻中,采用了深度优先搜索方法.其应用背景是从地理测绘图中检测道路边界和房屋轮廓,采用自动方法生成数字地图.由于测绘图中的文字、符号常常与有意义的图像特征重叠,主曲线检测旨在从原始测绘图中获得"洁净"的特征图像.大量的实际图像实验表明,本算法效率高、鲁棒性强.除了地理测绘图外,该方法还可以用于文本处理中的其他领域,如在文字识别中,将字符与之相重叠的其他无用图像分离.更多还原

【Abstract】 This paper presented a new method for the detection of principal curves in complicated feature images. Based on the criteria of the shortest path of curves and directional deviation of paths, principal curve detection is carried out in graph domain. Depth first search(DFS) searching scheme is adopted in exploration of a graph network. The motivation of this research is to find road boundaries and house contours from printed map images. Since characters and map symbols often overlap with useful image features, the algorithm of principal curve detection aims to obtain "clean" feature images from the original maps. By extensive experiments, the algorithm shows good efficiency and robustness with real map images. The technique described in this paper can also be used in other applications, such as in character recognition, to separate characters from other unwanted document components that overlap with the characters.更多还原