Presentation 2013-09-12
Unsupervised Structuring Element Estimation of Morphological Opening and Closing with GA
Yosuke NABETANI, Mitsuji MUNEYASU, Akira ASANO,
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Abstract(in English) In this paper, we propose an unsupervised design method for optimal structuring element (SE) of morphological filters. We formulate the design of SE as an optimization problem, and estimate an optimal shape and brightness of SE directly from degraded images. We estimated an optimal shape and brightness by using a Genetic Algorithm (GA). Estimation of SE that can remove noise while preserving original signals is achieved by objective function that use Rank-Ordered Logarithmic Differences (ROLD) statistic for the impulse noise detection.
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Keyword(in English) opening / ROLD / structuring element / genetic algorithm / mathematical morphology
Paper # SIS2013-20
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Committee SIS
Conference Date 2013/9/5(1days)
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Language JPN
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Title (in English) Unsupervised Structuring Element Estimation of Morphological Opening and Closing with GA
Sub Title (in English)
Keyword(1) opening
Keyword(2) ROLD
Keyword(3) structuring element
Keyword(4) genetic algorithm
Keyword(5) mathematical morphology
1st Author's Name Yosuke NABETANI
1st Author's Affiliation Faculty of Engineering Science, Kansai University()
2nd Author's Name Mitsuji MUNEYASU
2nd Author's Affiliation Faculty of Engineering Science, Kansai University
3rd Author's Name Akira ASANO
3rd Author's Affiliation Faculty of Informatics, Kansai University
Date 2013-09-12
Paper # SIS2013-20
Volume (vol) vol.113
Number (no) 202
Page pp.pp.-
#Pages 6
Date of Issue