Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition
Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scann...
Ausführliche Beschreibung
Autor*in: |
Yu, Lei [verfasserIn] |
---|
Format: |
Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2010 |
---|
Schlagwörter: |
---|
Anmerkung: |
© Springer-Verlag 2010 |
---|
Übergeordnetes Werk: |
Enthalten in: Wood science and technology - Springer-Verlag, 1967, 45(2010), 3 vom: 25. Mai, Seite 511-519 |
---|---|
Übergeordnetes Werk: |
volume:45 ; year:2010 ; number:3 ; day:25 ; month:05 ; pages:511-519 |
Links: |
---|
DOI / URN: |
10.1007/s00226-010-0341-7 |
---|
Katalog-ID: |
OLC2073072364 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | OLC2073072364 | ||
003 | DE-627 | ||
005 | 20230323230129.0 | ||
007 | tu | ||
008 | 200819s2010 xx ||||| 00| ||eng c | ||
024 | 7 | |a 10.1007/s00226-010-0341-7 |2 doi | |
035 | |a (DE-627)OLC2073072364 | ||
035 | |a (DE-He213)s00226-010-0341-7-p | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 670 |q VZ |
084 | |a 23 |2 ssgn | ||
100 | 1 | |a Yu, Lei |e verfasserin |4 aut | |
245 | 1 | 0 | |a Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition |
264 | 1 | |c 2010 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
338 | |a Band |b nc |2 rdacarrier | ||
500 | |a © Springer-Verlag 2010 | ||
520 | |a Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. | ||
650 | 4 | |a Fractal Brownian Motion | |
650 | 4 | |a Fractal Parameter | |
650 | 4 | |a Edge Point | |
650 | 4 | |a Compute Tomography System | |
650 | 4 | |a Multifractal Spectrum | |
700 | 1 | |a Qi, Dawei |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Wood science and technology |d Springer-Verlag, 1967 |g 45(2010), 3 vom: 25. Mai, Seite 511-519 |w (DE-627)129600679 |w (DE-600)241313-9 |w (DE-576)015094227 |x 0043-7719 |7 nnns |
773 | 1 | 8 | |g volume:45 |g year:2010 |g number:3 |g day:25 |g month:05 |g pages:511-519 |
856 | 4 | 1 | |u https://doi.org/10.1007/s00226-010-0341-7 |z lizenzpflichtig |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_OLC | ||
912 | |a SSG-OLC-TEC | ||
912 | |a SSG-OLC-CHE | ||
912 | |a SSG-OLC-FOR | ||
912 | |a SSG-OPC-FOR | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_2004 | ||
912 | |a GBV_ILN_2006 | ||
912 | |a GBV_ILN_2016 | ||
912 | |a GBV_ILN_2018 | ||
912 | |a GBV_ILN_2542 | ||
912 | |a GBV_ILN_4046 | ||
912 | |a GBV_ILN_4277 | ||
912 | |a GBV_ILN_4330 | ||
951 | |a AR | ||
952 | |d 45 |j 2010 |e 3 |b 25 |c 05 |h 511-519 |
author_variant |
l y ly d q dq |
---|---|
matchkey_str |
article:00437719:2010----::pligutfatlpcrmobndihrcadsrtbonamtomd |
hierarchy_sort_str |
2010 |
publishDate |
2010 |
allfields |
10.1007/s00226-010-0341-7 doi (DE-627)OLC2073072364 (DE-He213)s00226-010-0341-7-p DE-627 ger DE-627 rakwb eng 670 VZ 23 ssgn Yu, Lei verfasserin aut Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. Fractal Brownian Motion Fractal Parameter Edge Point Compute Tomography System Multifractal Spectrum Qi, Dawei aut Enthalten in Wood science and technology Springer-Verlag, 1967 45(2010), 3 vom: 25. Mai, Seite 511-519 (DE-627)129600679 (DE-600)241313-9 (DE-576)015094227 0043-7719 nnns volume:45 year:2010 number:3 day:25 month:05 pages:511-519 https://doi.org/10.1007/s00226-010-0341-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR SSG-OPC-FOR GBV_ILN_40 GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2016 GBV_ILN_2018 GBV_ILN_2542 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4330 AR 45 2010 3 25 05 511-519 |
spelling |
10.1007/s00226-010-0341-7 doi (DE-627)OLC2073072364 (DE-He213)s00226-010-0341-7-p DE-627 ger DE-627 rakwb eng 670 VZ 23 ssgn Yu, Lei verfasserin aut Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. Fractal Brownian Motion Fractal Parameter Edge Point Compute Tomography System Multifractal Spectrum Qi, Dawei aut Enthalten in Wood science and technology Springer-Verlag, 1967 45(2010), 3 vom: 25. Mai, Seite 511-519 (DE-627)129600679 (DE-600)241313-9 (DE-576)015094227 0043-7719 nnns volume:45 year:2010 number:3 day:25 month:05 pages:511-519 https://doi.org/10.1007/s00226-010-0341-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR SSG-OPC-FOR GBV_ILN_40 GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2016 GBV_ILN_2018 GBV_ILN_2542 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4330 AR 45 2010 3 25 05 511-519 |
allfields_unstemmed |
10.1007/s00226-010-0341-7 doi (DE-627)OLC2073072364 (DE-He213)s00226-010-0341-7-p DE-627 ger DE-627 rakwb eng 670 VZ 23 ssgn Yu, Lei verfasserin aut Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. Fractal Brownian Motion Fractal Parameter Edge Point Compute Tomography System Multifractal Spectrum Qi, Dawei aut Enthalten in Wood science and technology Springer-Verlag, 1967 45(2010), 3 vom: 25. Mai, Seite 511-519 (DE-627)129600679 (DE-600)241313-9 (DE-576)015094227 0043-7719 nnns volume:45 year:2010 number:3 day:25 month:05 pages:511-519 https://doi.org/10.1007/s00226-010-0341-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR SSG-OPC-FOR GBV_ILN_40 GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2016 GBV_ILN_2018 GBV_ILN_2542 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4330 AR 45 2010 3 25 05 511-519 |
allfieldsGer |
10.1007/s00226-010-0341-7 doi (DE-627)OLC2073072364 (DE-He213)s00226-010-0341-7-p DE-627 ger DE-627 rakwb eng 670 VZ 23 ssgn Yu, Lei verfasserin aut Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. Fractal Brownian Motion Fractal Parameter Edge Point Compute Tomography System Multifractal Spectrum Qi, Dawei aut Enthalten in Wood science and technology Springer-Verlag, 1967 45(2010), 3 vom: 25. Mai, Seite 511-519 (DE-627)129600679 (DE-600)241313-9 (DE-576)015094227 0043-7719 nnns volume:45 year:2010 number:3 day:25 month:05 pages:511-519 https://doi.org/10.1007/s00226-010-0341-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR SSG-OPC-FOR GBV_ILN_40 GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2016 GBV_ILN_2018 GBV_ILN_2542 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4330 AR 45 2010 3 25 05 511-519 |
allfieldsSound |
10.1007/s00226-010-0341-7 doi (DE-627)OLC2073072364 (DE-He213)s00226-010-0341-7-p DE-627 ger DE-627 rakwb eng 670 VZ 23 ssgn Yu, Lei verfasserin aut Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2010 Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. Fractal Brownian Motion Fractal Parameter Edge Point Compute Tomography System Multifractal Spectrum Qi, Dawei aut Enthalten in Wood science and technology Springer-Verlag, 1967 45(2010), 3 vom: 25. Mai, Seite 511-519 (DE-627)129600679 (DE-600)241313-9 (DE-576)015094227 0043-7719 nnns volume:45 year:2010 number:3 day:25 month:05 pages:511-519 https://doi.org/10.1007/s00226-010-0341-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR SSG-OPC-FOR GBV_ILN_40 GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2016 GBV_ILN_2018 GBV_ILN_2542 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4330 AR 45 2010 3 25 05 511-519 |
language |
English |
source |
Enthalten in Wood science and technology 45(2010), 3 vom: 25. Mai, Seite 511-519 volume:45 year:2010 number:3 day:25 month:05 pages:511-519 |
sourceStr |
Enthalten in Wood science and technology 45(2010), 3 vom: 25. Mai, Seite 511-519 volume:45 year:2010 number:3 day:25 month:05 pages:511-519 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Fractal Brownian Motion Fractal Parameter Edge Point Compute Tomography System Multifractal Spectrum |
dewey-raw |
670 |
isfreeaccess_bool |
false |
container_title |
Wood science and technology |
authorswithroles_txt_mv |
Yu, Lei @@aut@@ Qi, Dawei @@aut@@ |
publishDateDaySort_date |
2010-05-25T00:00:00Z |
hierarchy_top_id |
129600679 |
dewey-sort |
3670 |
id |
OLC2073072364 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2073072364</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230323230129.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2010 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00226-010-0341-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2073072364</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00226-010-0341-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">23</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Yu, Lei</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2010</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag 2010</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fractal Brownian Motion</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fractal Parameter</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Edge Point</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Compute Tomography System</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multifractal Spectrum</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qi, Dawei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Wood science and technology</subfield><subfield code="d">Springer-Verlag, 1967</subfield><subfield code="g">45(2010), 3 vom: 25. Mai, Seite 511-519</subfield><subfield code="w">(DE-627)129600679</subfield><subfield code="w">(DE-600)241313-9</subfield><subfield code="w">(DE-576)015094227</subfield><subfield code="x">0043-7719</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:45</subfield><subfield code="g">year:2010</subfield><subfield code="g">number:3</subfield><subfield code="g">day:25</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:511-519</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00226-010-0341-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2016</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2542</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4277</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4330</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">45</subfield><subfield code="j">2010</subfield><subfield code="e">3</subfield><subfield code="b">25</subfield><subfield code="c">05</subfield><subfield code="h">511-519</subfield></datafield></record></collection>
|
author |
Yu, Lei |
spellingShingle |
Yu, Lei ddc 670 ssgn 23 misc Fractal Brownian Motion misc Fractal Parameter misc Edge Point misc Compute Tomography System misc Multifractal Spectrum Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition |
authorStr |
Yu, Lei |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)129600679 |
format |
Article |
dewey-ones |
670 - Manufacturing |
delete_txt_mv |
keep |
author_role |
aut aut |
collection |
OLC |
remote_str |
false |
illustrated |
Not Illustrated |
issn |
0043-7719 |
topic_title |
670 VZ 23 ssgn Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition Fractal Brownian Motion Fractal Parameter Edge Point Compute Tomography System Multifractal Spectrum |
topic |
ddc 670 ssgn 23 misc Fractal Brownian Motion misc Fractal Parameter misc Edge Point misc Compute Tomography System misc Multifractal Spectrum |
topic_unstemmed |
ddc 670 ssgn 23 misc Fractal Brownian Motion misc Fractal Parameter misc Edge Point misc Compute Tomography System misc Multifractal Spectrum |
topic_browse |
ddc 670 ssgn 23 misc Fractal Brownian Motion misc Fractal Parameter misc Edge Point misc Compute Tomography System misc Multifractal Spectrum |
format_facet |
Aufsätze Gedruckte Aufsätze |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
nc |
hierarchy_parent_title |
Wood science and technology |
hierarchy_parent_id |
129600679 |
dewey-tens |
670 - Manufacturing |
hierarchy_top_title |
Wood science and technology |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)129600679 (DE-600)241313-9 (DE-576)015094227 |
title |
Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition |
ctrlnum |
(DE-627)OLC2073072364 (DE-He213)s00226-010-0341-7-p |
title_full |
Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition |
author_sort |
Yu, Lei |
journal |
Wood science and technology |
journalStr |
Wood science and technology |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
600 - Technology |
recordtype |
marc |
publishDateSort |
2010 |
contenttype_str_mv |
txt |
container_start_page |
511 |
author_browse |
Yu, Lei Qi, Dawei |
container_volume |
45 |
class |
670 VZ 23 ssgn |
format_se |
Aufsätze |
author-letter |
Yu, Lei |
doi_str_mv |
10.1007/s00226-010-0341-7 |
dewey-full |
670 |
title_sort |
applying multifractal spectrum combined with fractal discrete brownian motion model to wood defects recognition |
title_auth |
Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition |
abstract |
Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. © Springer-Verlag 2010 |
abstractGer |
Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. © Springer-Verlag 2010 |
abstract_unstemmed |
Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood. © Springer-Verlag 2010 |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-CHE SSG-OLC-FOR SSG-OPC-FOR GBV_ILN_40 GBV_ILN_70 GBV_ILN_2004 GBV_ILN_2006 GBV_ILN_2016 GBV_ILN_2018 GBV_ILN_2542 GBV_ILN_4046 GBV_ILN_4277 GBV_ILN_4330 |
container_issue |
3 |
title_short |
Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition |
url |
https://doi.org/10.1007/s00226-010-0341-7 |
remote_bool |
false |
author2 |
Qi, Dawei |
author2Str |
Qi, Dawei |
ppnlink |
129600679 |
mediatype_str_mv |
n |
isOA_txt |
false |
hochschulschrift_bool |
false |
doi_str |
10.1007/s00226-010-0341-7 |
up_date |
2024-07-03T17:09:56.652Z |
_version_ |
1803578608609918976 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2073072364</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230323230129.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2010 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00226-010-0341-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2073072364</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s00226-010-0341-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">23</subfield><subfield code="2">ssgn</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Yu, Lei</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Applying multifractal spectrum combined with fractal discrete Brownian motion model to wood defects recognition</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2010</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag 2010</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Wood nondestructive testing technology is a new and multidisciplinary industry scientific research. It has attained fast development and achievements in recent years. X-ray computed tomography (CT) scanning technology is a kind of wood nondestructive testing technology in practice. CT scanning technology has been applied to the detection of internal defects in the logs for the purpose of obtaining prior information, which can be used to reach better wood sawing decision. Fractal geometry and its extension multifractal are used for describing, modeling, analyzing, and processing of different complex shapes and images. A method in CT image edge detection using multifractal theory combined with fractal Brownian motion is applied in the paper. First, its multifractal spectrum is estimated. Then, different types of pixels are classified by the spectrum; they are smoothing edge points and singular edge points. From the images processed by multifractal spectrum theory and compared with each image by different spectrum values, it can be seen that the larger the range of threshold is set, the more exact the edge can be detected. The paper provides a new method to recognize the defect information and to saw it in the condition of nondestructive wood.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fractal Brownian Motion</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fractal Parameter</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Edge Point</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Compute Tomography System</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Multifractal Spectrum</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Qi, Dawei</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Wood science and technology</subfield><subfield code="d">Springer-Verlag, 1967</subfield><subfield code="g">45(2010), 3 vom: 25. Mai, Seite 511-519</subfield><subfield code="w">(DE-627)129600679</subfield><subfield code="w">(DE-600)241313-9</subfield><subfield code="w">(DE-576)015094227</subfield><subfield code="x">0043-7719</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:45</subfield><subfield code="g">year:2010</subfield><subfield code="g">number:3</subfield><subfield code="g">day:25</subfield><subfield code="g">month:05</subfield><subfield code="g">pages:511-519</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">https://doi.org/10.1007/s00226-010-0341-7</subfield><subfield code="z">lizenzpflichtig</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-CHE</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-FOR</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2016</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2542</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4046</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4277</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4330</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">45</subfield><subfield code="j">2010</subfield><subfield code="e">3</subfield><subfield code="b">25</subfield><subfield code="c">05</subfield><subfield code="h">511-519</subfield></datafield></record></collection>
|
score |
7.3976154 |