Presentation | 1996/1/19 Extraction of Singular Locations from an Image Using Immune Network Kazuya KUBO, Toshio ITO, Yukio KANEDA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | We take the distributed diagnostic model as an Immune Network Model and applies it to image processing. The Immune System is composed of units, each of which has several states and can test other units to identify faulty ones among them in the whole system. This model is suitable for parallel processing. At first, we define line patterns extracted by using local Hough Transform as units and introduce several dynamical model into them to extract such blurred locations as blotted spots or noise. Then we compare those locations with contours. Secondly, modeled features boundary, in particular,the boundary of two textures which are modeled as a 2-D Markov Random Fields is extracted. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | immune network / blurred image / contours / boundary extraction / Markov Random Fields |
Paper # | PRU95-209 |
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Committee | PRU |
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Conference Date | 1996/1/19(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Understanding (PRU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Extraction of Singular Locations from an Image Using Immune Network |
Sub Title (in English) | |
Keyword(1) | immune network |
Keyword(2) | blurred image |
Keyword(3) | contours |
Keyword(4) | boundary extraction |
Keyword(5) | Markov Random Fields |
1st Author's Name | Kazuya KUBO |
1st Author's Affiliation | The Graduate School of Science and Technology, Kobe University() |
2nd Author's Name | Toshio ITO |
2nd Author's Affiliation | Electronics Engineering Div.,Daihatsu Motor Co.,Ltd. |
3rd Author's Name | Yukio KANEDA |
3rd Author's Affiliation | Faculty of Engineering, Kobe University |
Date | 1996/1/19 |
Paper # | PRU95-209 |
Volume (vol) | vol.95 |
Number (no) | 470 |
Page | pp.pp.- |
#Pages | 6 |
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