2006 Fiscal Year Final Research Report Summary
New methods for signal and image processing by information theoretic divergence
| Project/Area Number |
15500191
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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 |
Statistical science
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| Research Institution | Kinki University |
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Principal Investigator |
KIKKAWA Sho Kinki University, School of Biology-Oriented Science and Technology, Reseach Fellow, 生物理工学部, 研究員 (30075329)
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| Co-Investigator(Kenkyū-buntansha) |
YOSHIDA Hisashi Kinki University, School of Biology-Oriented Science and Technology, Associate Professor, 生物理工学部, 助教授 (50278735)
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| Project Period (FY) |
2003 – 2006
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| Keywords | Renyi's a-order entropy / equivalent bandwidth / optimum threshold / hiden-variable / mutual infromation / divergenc / error probability / model-fitting |
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| Research Abstract |
1. We proposed a unified class of equivalent bandwidths of a random process by using Renyi's a-order entropy. It is useful to evaluate randomness of a random process.
2. We investigated global thresholding of a image. In addition to traditional one-step methods, we proposed a new idea of the two-steps method. In the first step of the method, you estimate the optimum model probability distribution that the grey-level variable obeys and in the second step you decide the optimum threshold to binarize the image. We propose a new binarization-oriented method for model distriobution fitting where we introduce class labels as hiden-variable and, instead of the traditional divergence measure, information theoretic mutual information measure is used. Simulation experiments shows our methodes are very powerful.
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Research Products
(34 results)
