| Project/Area Number |
61550259
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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 |
計算機工学
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| Research Institution | Shizuoka University |
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Principal Investigator |
ABE Keiichi Shizuoka University, 工学部, 教授 (80022193)
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| Co-Investigator(Kenkyū-buntansha) |
NAKATANI Hiromasa Shizuoka University, 工学部, 助教授 (80109131)
OGAWA Hideo Fukui University, 教育学部, 助教授 (90092824)
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| Project Period (FY) |
1986 – 1987
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| Project Status |
Completed (Fiscal Year 1987)
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| Budget Amount *help |
¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 1987: ¥400,000 (Direct Cost: ¥400,000)
Fiscal Year 1986: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | shape analysis of binary images / structural analysis of binary images / geometric properties / feature points of line patterns / symmetry / thinning / 図面認識 / 幾化学的特徴 / 3次元空間構造の解析 |
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| Research Abstract |
1. Comparison of methods for extracting feature points from line patterns
Five methods for extracting corner points, inflection points, and points connecting a straight line with a curve. Wxperiments are made on flowchart symbols handwritten with templates. The results depict merits and demerits of each method.
2. New algorithms for shape analysis of binary images
A new method for detecting corner points on digital curves is developed based on local symmetry of the shape. Experiments reveal that the method yields intuitively reasonable results independent of the applied parameter values. The axes of symmetry can be determined by evaluating the extent of symmetry among the detected corner points. This method can be applied to even deformed or partially occluded figures.Decomposing line patterns into line segments at corner points and matching those segments leads to a definition of similarity between two line patterns.
3. Fast thinning and structural analysis algorithms
Two fast thinning algorithms for binary images are developed: one is sequential type using distance transformation and the other is 2-subcycle parallel processing type. A combined sequential-parallel thinning algorithm for gray-level images are also proposed, which is useful for structural analysis of gray-level images. A method for decomposing a binary image into meaningful parts is being developed.
4. Structure understanding of a diagram
Discrimination of symbols, flow lines, and characters in a handwritten flowchart image is investigated. Methods for detecting feature points in diagram images without thinning are studied experimentally. A control mechanism for transferring between local substructure recognition and global consistency check is proposed.
5. Shape analysis in color images
A project started for applying shape analysis method thus developed to understanding color images and matching two color images in stereo vision.
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