Study on a high-level processing for large size image using a effective geometrical graphic data structure
Project/Area Number |
61460233
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Research Category |
Grant-in-Aid for General Scientific Research (B)
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Allocation Type | Single-year Grants |
Research Field |
Informatics
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Research Institution | University of Tokyo |
Principal Investigator |
OHSAWA Yutaka (1987) Assistant professor, Univ. of Tokyo, 生産技術研究所, 助手 (50152111)
坂内 正夫 (1986) 東大, 生産技術研究所, 助教授 (30107370)
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Co-Investigator(Kenkyū-buntansha) |
TAKABA Sadao Professor, Univ. of Tokyo, 生産技術研究所, 教授 (50013107)
大沢 裕 東京大学, 生産技術研究所, 助手 (50152111)
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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 |
¥5,600,000 (Direct Cost: ¥5,600,000)
Fiscal Year 1987: ¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 1986: ¥3,800,000 (Direct Cost: ¥3,800,000)
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Keywords | Image Processing / Graphical data structure / Drawing Processor / Pattern Database BD tree / カラー画像の限定色表示 / コンピューターグラフィックス / 画像認識・理解 / 画像処理 / パターンデータ構造 / 図面処理 |
Research Abstract |
A new type of software-based image processing technique is proposed and investigated in this paper, which can realize very high efficiency and intelligence especially for large size (or large volume)image data such as various types of drawings and color images. In the first stage of the project, an efficient general purpose data structure suitable for 2 of 3 dimensional graphical primitives (lines, areas, volumes etc.),named the BD tree(graphic),has been introduced by devised extension of a multi-dimensional data structure BD tree which was proposed uniquely by this research group in 1983. Effectiveness of this graphical data structure has been revealed from the viewpoint of memory usage and retrieval efficiency through many computer simulations using a various types of real map data. In the next stage, a general framework for software-based large image processing has been proposed and evaluated. Large image data, typically 8000 by 6000 pixels coded by run-length method, are first conver
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ted into appropriate graphical primitives such as contour vectors by our unique method, which are then inserted bynamically to the BD tree(graphics) as preparation for hereafter processing. All the required image processing functions can be performed by a efficient and intelligent geometric operations on the graphical primitives representing the original image. Abstraction level for original graphical primitives are gradually enhanced through core vector level, higher graphical primitive level such as circle, and finally semantically recognized level. A drawing processor, the AI-MUDAMS is implemented using portable language C as a concrete embodiment of this general frame-work. In final, a new color selection technique using a similar framework using the extended threedimensional BD tree has been also proposed. Many experiments, including 16-color 256-dolor selection from 16 million color images in the Japanese Academic standard image database, SIDBA, reveals the superiority of the proposed method to other existing methods. Less
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Report
(2 results)
Research Products
(16 results)