Development of a new detection method of image primitives by several procedures in image space and parameter space
Project/Area Number |
22500156
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Perception information processing/Intelligent robotics
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Research Institution | Ehime University |
Principal Investigator |
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Project Period (FY) |
2010-10-20 – 2014-03-31
|
Project Status |
Completed (Fiscal Year 2013)
|
Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2013: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2012: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2011: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2010: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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Keywords | 画像解析 / 直線抽出 / 円・楕円抽出 / 画像プリミティブ / ハフ変換 / 画像処理 / 画像認識 / 画像理解 |
Research Abstract |
In image analysis, it is important to detect straight lines, circles and ellipses which exist in the image and are called image primitives, because these image primitives represent edges of the objects in the image. The most popular technique to detect the image primitives is Hough transform. At the transform, resulting peaks in the accumulator array which are gotten by a voting procedure in the parameter space represent strong evidence that a corresponding the image primitives exist in the image. In the voting procedure, a large number of votes are necessary and it makes the transform slow. In this research, we developed speed-up methods which reduce the parameter space and remove the unnecessary vote by introducing several procedures at the image space. From the experimental results and theoretical analysis, we confirmed that the developed methods have good performance.
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Report
(5 results)
Research Products
(35 results)