Basic Study on Automatic Drawing Input System and Evaluation Method for Recognition Results

图形自动输入是建立地理信息系统(GIS)和图形数据库系统的关键技术。根据几个正在开发和广泛使用的商用系统，用户希望对这些系统进行比较，以选择更好的系统。然而，到目前为止，在图形输入领域还没有普遍接受的评价标准。本研究的目的之一是建立图形输入系统之间比较的标准方法，另一个目的是促进自动图形输入系统的发展。为了比较计算机系统之间的性能，提出了几种基准测试并得到了广泛应用。基准图的提出是为了比较不同的图形输入系统，不同的应用和不同的图形类型，图形输入的目的和图形的性质是不同的。在本研究中，选取了MAP，提出了该评价方法的必要性。本研究将该对象的地图称为基准地图，在地图的选择上，考虑了地图包含各种地理符号和描绘典型地面形态的情况。被选为基准的地图如下：(1)1/25000的一部分Ojiya地图，(2)1/25000东京-SYUBU地图的一部分，(3)1/2500 Tottori地图的一部分。(1)和(2)在地图上选择15厘米×12厘米的部分，以及(3)选择地图的23厘米×18厘米的部分。本研究的另一个主题是提出一种快速且健壮的绘图矢量化方法。针对这一问题，提出了一种核线提取和细化相结合的矢量化方法。然后，通过实验证明了该方法的良好特性。

Automatic drawing input is an essential technique to build geographic information systems (GIS) and drawing databased systems. According to several commercial based systems being developed and widely used, the users wants to compare these systems to chose better one. The evaluation standard widely accepted, however, dose not exist on the field of drawing input, until now. One of the objecta of this research is to establish a standard method for comparison among drawing input systems, and another object is to advance automatic drawing input systems.To compare the performance among computer systems, several kinds of benchmark tests are proposed and widely used. In this study, benchmark drawings are proposed for the sake of mutual comparision of drawing input systems.The purpose of the drawing input and the nature of the drawings are quit different from the applications and the kind of the drawings. In this research, map is selected to propose the necessity of the evaluation method. The maps for this object are called benchmark maps, in this research.On the selection of the maps, the condition which the maps include various geographical symbols and depicted typical configuration of the ground were considered. The maps selected for benchmark are the followings ; (1) a part of 1/25000 map OJIYA, (2) a part of 1/25000 map TOKYO-SYUBU, (3) a pat of 1/2500 map TOTTORI.(1) and (2) are selected 15cm x 12cm part on the maps, and (3) is selected 23cm x 18cm part of the map. The answer vector data were made by hand-digitizing, and an evaluation method used benchmarks maps and the answer data proposed.Another topic of this research is to propose a fast and robust drawing vectrization method. For this object, a vectorization method using a combination of core-line extraction and thinning is proposed. Then, the good features of the proposed method are presented by experiments.