Directional variance analysis of annual rings
The wood quality measurement methods are of increasing importance in the wood industry. The goal is to produce more high quality products with higher marketing value than is produced today. One of the key factors for increasing the market value is to provide better measurements for increased informa...
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Veröffentlicht in: | Journal of physics. Conference series 2010-07, Vol.238 (1), p.012047 |
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description | The wood quality measurement methods are of increasing importance in the wood industry. The goal is to produce more high quality products with higher marketing value than is produced today. One of the key factors for increasing the market value is to provide better measurements for increased information to support the decisions made later in the product chain. Strength and stiffness are important properties of the wood. They are related to mean annual ring width and its deviation. These indicators can be estimated from images taken from the log ends by two-dimensional power spectrum analysis. The spectrum analysis has been used successfully for images of pine. However, the annual rings in birch, for example are less distinguishable and the basic spectrum analysis method does not give reliable results. A novel method for local log end variance analysis based on Radon-transform is proposed. The directions and the positions of the annual rings can be estimated from local minimum and maximum variance estimates. Applying the spectrum analysis on the maximum local variance estimate instead of the original image produces more reliable estimate of the annual ring width. The proposed method is not limited to log end analysis only. It is usable in other two-dimensional random signal and texture analysis tasks. |
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The goal is to produce more high quality products with higher marketing value than is produced today. One of the key factors for increasing the market value is to provide better measurements for increased information to support the decisions made later in the product chain. Strength and stiffness are important properties of the wood. They are related to mean annual ring width and its deviation. These indicators can be estimated from images taken from the log ends by two-dimensional power spectrum analysis. The spectrum analysis has been used successfully for images of pine. However, the annual rings in birch, for example are less distinguishable and the basic spectrum analysis method does not give reliable results. A novel method for local log end variance analysis based on Radon-transform is proposed. The directions and the positions of the annual rings can be estimated from local minimum and maximum variance estimates. 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Conference series</title><description>The wood quality measurement methods are of increasing importance in the wood industry. The goal is to produce more high quality products with higher marketing value than is produced today. One of the key factors for increasing the market value is to provide better measurements for increased information to support the decisions made later in the product chain. Strength and stiffness are important properties of the wood. They are related to mean annual ring width and its deviation. These indicators can be estimated from images taken from the log ends by two-dimensional power spectrum analysis. The spectrum analysis has been used successfully for images of pine. However, the annual rings in birch, for example are less distinguishable and the basic spectrum analysis method does not give reliable results. A novel method for local log end variance analysis based on Radon-transform is proposed. The directions and the positions of the annual rings can be estimated from local minimum and maximum variance estimates. Applying the spectrum analysis on the maximum local variance estimate instead of the original image produces more reliable estimate of the annual ring width. The proposed method is not limited to log end analysis only. It is usable in other two-dimensional random signal and texture analysis tasks.</description><subject>Market value</subject><subject>Measurement methods</subject><subject>Physics</subject><subject>Power spectrum analysis</subject><subject>Quality assessment</subject><subject>Random signals</subject><subject>Spectrum analysis</subject><subject>Stiffness</subject><subject>Two dimensional analysis</subject><subject>Variance analysis</subject><issn>1742-6596</issn><issn>1742-6588</issn><issn>1742-6596</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp9kE1LxDAQhoMouK7-BSl4rp2kzbQ9yvoJC170HKb5kCxrW5NdYf-9WSrqYTGXvMM873wxdsnhmkPTFLyuRI6yxUKUKSqAC6jqIzb7SRz_0afsLMYVQJlePWP5rQ9Wb_zQ0zr7pOCp1zajFO2ij9ngku63KRd8_xbP2YmjdbQX3_-cvd7fvSwe8-Xzw9PiZpnrUjab3AmDILFCgUYIBKNbsFRyWTljqKNOp0kRTZUkNYI0dlq2te2Ik6uRl3N2NdUdw_CxtXGjVsM2pKGiErIBwBJkmyicKB2GGIN1agz-ncJOcVD706j91mq_tUoNFVfTaZIxn4x-GH89B1k1Gpd4foD_v8cXBTRyWg</recordid><startdate>20100701</startdate><enddate>20100701</enddate><creator>Kumpulainen, P</creator><creator>Marjanen, K</creator><general>IOP Publishing</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>H8D</scope><scope>HCIFZ</scope><scope>L7M</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20100701</creationdate><title>Directional variance analysis of annual rings</title><author>Kumpulainen, P ; Marjanen, K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c358t-f2d60564626d2260dc90ea3154fddababc23866d4baba82ac6bc597eba1af7613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Market value</topic><topic>Measurement methods</topic><topic>Physics</topic><topic>Power spectrum analysis</topic><topic>Quality assessment</topic><topic>Random signals</topic><topic>Spectrum analysis</topic><topic>Stiffness</topic><topic>Two dimensional analysis</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kumpulainen, P</creatorcontrib><creatorcontrib>Marjanen, K</creatorcontrib><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Aerospace Database</collection><collection>SciTech Premium Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Journal of physics. 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Strength and stiffness are important properties of the wood. They are related to mean annual ring width and its deviation. These indicators can be estimated from images taken from the log ends by two-dimensional power spectrum analysis. The spectrum analysis has been used successfully for images of pine. However, the annual rings in birch, for example are less distinguishable and the basic spectrum analysis method does not give reliable results. A novel method for local log end variance analysis based on Radon-transform is proposed. The directions and the positions of the annual rings can be estimated from local minimum and maximum variance estimates. Applying the spectrum analysis on the maximum local variance estimate instead of the original image produces more reliable estimate of the annual ring width. The proposed method is not limited to log end analysis only. 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subjects | Market value Measurement methods Physics Power spectrum analysis Quality assessment Random signals Spectrum analysis Stiffness Two dimensional analysis Variance analysis |
title | Directional variance analysis of annual rings |
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