2003 Fiscal Year Final Research Report Summary
RESEARCH ON ACTIVE CONTOUR MODELS USING A PRIORI KNOWLEDGE OBTAINED FROM AN INITIAL CONTOUR
| Project/Area Number |
14580441
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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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 | TOHOKU UNIVERSITY |
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Principal Investigator |
ABE Toru Tohoku University, Information synergy Center, Associate Professor, 情報シナジーセンター, 助教授 (80222652)
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| Project Period (FY) |
2002 – 2003
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| Keywords | image processing / region extraction / active contour model / a priori knowledge / shape information / symbolic description |
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| Research Abstract |
Region extraction from images is an important topic in image processing. For this issue, active contour model (ACM) has achieved considerable success.
In region extraction with ACM, a user first draws a contour C around a target region and defines its evaluation (energy) function B. This C is iteratively deformed so as to decreases B, and the deformed C that minimizes E is extracted as a target region boundary. Since naive ACM evaluates only the certainty that C is located on a region boundary, when an image has several object regions, there is no guarantee that C is deformed to correspond with the target region boundary. To solve this problem, several methods have been proposed for employing the a priori knowledge of a target region shape. However, the existing methods need the making of prototypes or training with samples, and thus they require time-consuming preparation work and impose tight restrictions on their target regions.
To overcome the difficulties in the existing methods, we propose a novel method for employing the a priori knowledge of a target region shape. The proposed method is based on an idea that an initial value of C (an initial contour Cini drawn around a target region by a user) can include the shape features of a target region. In this method, the sequence of shape features (such as corner, line, and curve) is obtained from Cini. This sequence is encoded into a symbolic description and used as the a priori knowledge of a target region shape. During region extraction procedure, by finding the optimal assignment of the symbols (shape features) to the control points of C and determining the optimal positions for these points, the a priori knowledge is reflected on the extracted region shape.
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Research Products
(12 results)
