| Project/Area Number |
06555049
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 試験 |
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| Research Field |
設計工学・機械要素・トライボロジー
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| Research Institution | TOKYO METROPOLITAN INSTITUTE OF TECHNOLOGY |
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Principal Investigator |
FUKUDA Shuichi TOKYO METROPOLITAN INSTITUTE OF TECHNOLOGY DEPARTMENT OF PRODUCTION,INFORMATION AND SYSTEMS ENGINEERING, 工学部, 教授 (90107095)
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| Co-Investigator(Kenkyū-buntansha) |
IKEI Yasushi TOKYO METROPOLITAN INSTITUTE OF TECHNOLOGY DEPARTMENT OF PRODUCTION,INFORMATION, 工学部, 助教授 (00202870)
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| Project Period (FY) |
1994 – 1996
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| Project Status |
Completed (Fiscal Year 1996)
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| Budget Amount *help |
¥7,000,000 (Direct Cost: ¥7,000,000)
Fiscal Year 1996: ¥1,300,000 (Direct Cost: ¥1,300,000)
Fiscal Year 1995: ¥2,200,000 (Direct Cost: ¥2,200,000)
Fiscal Year 1994: ¥3,500,000 (Direct Cost: ¥3,500,000)
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| Keywords | Image Separation / Natural Images and Artificial Images / Fractal Dimension / Integer Dimension and Non-integer Dimension / Binary Images / Color Images / ASIC / イメージプロセッシング / 画像弁別 / 人工物画像 / 自然物画像 / プリプロセッシング |
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| Research Abstract |
If we can separate artificial and natural images, a robot can easily navigate even if the scene may change from season to season because of the falling leaves, etc. , since those images which change from season to season are natural ones and those which do not are artificial ones. And we can easily detect cracks in a very complex structure without any prior knowledge because cracks are natural in nature.
In this work, we noticed that natural images have non-integer Fractal dimensions and artificial ones have integer dimensions and developed the methodology and conceptual design for ASIC.
What we have done and achieved in this project are
(1) We calculate Fractal dimension using the box counting method.
(2) The following two methods are developed for binary images.
[Static separation method]
Divide the target image into meshes. The Fractal dimension is calculated segment by segment, which is a group of meshes. These local segments are grouped together by the value of Fractal dimension.
[Dynamic separation method]
The Fractal dimension is calculated moving dx in the x direction and dy in the y direction sequentially. By the size of the local segment and the size of dx and dy, overlap sometimes occurs. If such overlap occurs, Fractal dimension is calculated in terms of pixels and the average value of these valuse will be used.
(3) We extended the above method to color images.
We calculate the histogram for HSL (Hue, Saturation and Lightness) of the color image.
Then it is divided by peak based on the histogram. The same procedure as the binary image is applied for each color segments.
(4) We developed conceptual design for ASIC
The above methodology can also be applied to separation problems between artificial and natural sounds.
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