1994 Fiscal Year Final Research Report Summary
Basic Study on Automatic Drawing Input System and Evaluation Method for Recognition Results
| Project/Area Number |
05680310
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
情報システム学(含情報図書館学)
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| Research Institution | SAITAMA UNIBERSITY |
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Principal Investigator |
OHSAWA Yutaka Saitama University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (50152111)
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| Project Period (FY) |
1993 – 1994
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| Keywords | Automatic Drawing Input System / Digital Map / Drawing Recognition / Bench-mark / System Evaluation |
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| Research Abstract |
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.
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