IEEE Trans Image Process. 2017 Jun;26(6):2751-2766. doi: 10.1109/TIP.2016.2613409. Epub 2016 Sep 23.
It is difficult to separate the point symbols from the scanned topographic maps accurately, which brings challenges for the recognition of the point symbols. In this paper, based on the framework of generalized Hough transform (GHT), we propose a new algorithm, which is named shear line segment GHT (SLS-GHT), to recognize the point symbols directly in the scanned topographic maps. SLS-GHT combines the line segment GHT (LS-GHT) and the shear transformation. On the one hand, LS-GHT is proposed to represent the features of the point symbols more completely. Its R-table has double level indices, the first one is the color information of the point symbols, and the other is the slope of the line segment connected a pair of the skeleton points. On the other hand, the shear transformation is introduced to increase the directional features of the point symbols; it can make up for the directional limitation of LS-GHT indirectly. In this way, the point symbols are detected in a series of the sheared maps by LS-GHT, and the final optimal coordinates of the setpoints are gotten from a series of the recognition results. SLS-GHT detects the point symbols directly in the scanned topographic maps, totally different from the traditional pattern of extraction before recognition. Moreover, several experiments demonstrate that the proposed method allows improved recognition in complex scenes than the existing methods.
准确地从扫描的地形图中分离出点状符号具有一定难度，这给点状符号的识别带来了挑战。在本文中，基于广义霍夫变换（GHT）框架，我们提出了一种新的算法，称为剪切线段 GHT（SLS-GHT），用于直接在扫描的地形图中识别点状符号。SLS-GHT 结合了线段 GHT（LS-GHT）和剪切变换。一方面，LS-GHT 被提出用于更完整地表示点状符号的特征。它的 R 表具有双级索引，第一个索引是点状符号的颜色信息，另一个索引是连接一对骨架点的线段的斜率。另一方面，引入剪切变换来增加点状符号的方向特征；它可以间接弥补 LS-GHT 的方向局限性。通过 LS-GHT 在一系列剪切图像中检测点状符号，并从一系列识别结果中获取设定点的最终最佳坐标。SLS-GHT 直接在扫描的地形图中检测点状符号，与传统的识别前提取模式完全不同。此外，几项实验表明，与现有方法相比，该方法允许在复杂场景中提高识别能力。
