地形图的自动扫描矢量化是GIS领域亟待解决的一个重要难题。地形图中包含了大量的字体丰富的数字注记,用以表示地物地貌的属性等特征,正确提取并识别这些数字是图纸处理中的重要组成部分。本文分析了现有的提取方法的不足,提出了一种新的数字注记自动提取与识别算法,首先根据先验的尺寸大小确定候选数字,再采用OCON结构的BP神经网络识别出真正的数字,然后利用近邻关系提取出扩展数字。实验表明,该算法是快速、高效、可靠的。

Automatic vectorization of scanned topographic maps is an important and difficult problem that needs to be solved urgently. Atopographic map includes plenty of numbers with various fonts which indicate properties and other features of general configuration. Extracting and recognizing these numbers correctly is an important part in map disposal. Many present methods of extraction are analyzed on their disadvantages and a new extraction and recognition algorithm of numbers is presented in this paper. The algorithm first fixes on candidates according to transcendental sizes ,and then recognizes real numbers with BP neural network of OCON structure. At last ,it extracts extended numbers using relation of neighborhood. Experiments have proved it is fast ,efficient and reliable.