Intelligent musk identification method based on hyperspectral imaging and application
The invention provides an intelligent musk identification method based on hyperspectral imaging and application, and relates to the field of traditional Chinese medicinal material identification, the identification method comprises the following steps: constructing a musk quality identification mode...
Gespeichert in:
Hauptverfasser: | , , , , , , |
---|---|
Format: | Patent |
Sprache: | chi ; eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | |
container_volume | |
creator | CHE LI WANG YI ZHAN ZHIXUE HONG PENGXIONG ZHONG YI LAI ZHICHENG LIAO GENJIE |
description | The invention provides an intelligent musk identification method based on hyperspectral imaging and application, and relates to the field of traditional Chinese medicinal material identification, the identification method comprises the following steps: constructing a musk quality identification model: collecting hyperspectral data of a musk sample, obtaining a hyperspectral image, carrying out black and white correction processing, and intelligently selecting a region of interest by making a mask; calculating an average spectrum in the region of interest and carrying out spectrum preprocessing; constructing a musk identification model based on a machine learning algorithm; and based on the identification model, identifying the quality of the musk sample to complete the identification of the quality of the musk. The method and the identification model are applied to quality identification of musk products with different qualities, quality identification of musk can be completed intelligently, efficiently and n |
format | Patent |
fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN115937670A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN115937670A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN115937670A3</originalsourceid><addsrcrecordid>eNqNizEOwjAMRbMwIOAO5gBIVBVUHVEFgoUJ5sokbmqRuFFjBm5Phx6A6b8nvb80z5sohcCeRCF-8hvYTcgdW1QeBCJpPzh4YSYHk_ffRGNOZHXEABzRs3hAcYAphfm1NosOQ6bNvCuzvZwfzXVHaWgpJ7QkpG1zL4pDXVbHan8q_2l-QjY5-Q</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Intelligent musk identification method based on hyperspectral imaging and application</title><source>esp@cenet</source><creator>CHE LI ; WANG YI ; ZHAN ZHIXUE ; HONG PENGXIONG ; ZHONG YI ; LAI ZHICHENG ; LIAO GENJIE</creator><creatorcontrib>CHE LI ; WANG YI ; ZHAN ZHIXUE ; HONG PENGXIONG ; ZHONG YI ; LAI ZHICHENG ; LIAO GENJIE</creatorcontrib><description>The invention provides an intelligent musk identification method based on hyperspectral imaging and application, and relates to the field of traditional Chinese medicinal material identification, the identification method comprises the following steps: constructing a musk quality identification model: collecting hyperspectral data of a musk sample, obtaining a hyperspectral image, carrying out black and white correction processing, and intelligently selecting a region of interest by making a mask; calculating an average spectrum in the region of interest and carrying out spectrum preprocessing; constructing a musk identification model based on a machine learning algorithm; and based on the identification model, identifying the quality of the musk sample to complete the identification of the quality of the musk. The method and the identification model are applied to quality identification of musk products with different qualities, quality identification of musk can be completed intelligently, efficiently and n</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES ; MEASURING ; PHYSICS ; TESTING</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230407&DB=EPODOC&CC=CN&NR=115937670A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20230407&DB=EPODOC&CC=CN&NR=115937670A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>CHE LI</creatorcontrib><creatorcontrib>WANG YI</creatorcontrib><creatorcontrib>ZHAN ZHIXUE</creatorcontrib><creatorcontrib>HONG PENGXIONG</creatorcontrib><creatorcontrib>ZHONG YI</creatorcontrib><creatorcontrib>LAI ZHICHENG</creatorcontrib><creatorcontrib>LIAO GENJIE</creatorcontrib><title>Intelligent musk identification method based on hyperspectral imaging and application</title><description>The invention provides an intelligent musk identification method based on hyperspectral imaging and application, and relates to the field of traditional Chinese medicinal material identification, the identification method comprises the following steps: constructing a musk quality identification model: collecting hyperspectral data of a musk sample, obtaining a hyperspectral image, carrying out black and white correction processing, and intelligently selecting a region of interest by making a mask; calculating an average spectrum in the region of interest and carrying out spectrum preprocessing; constructing a musk identification model based on a machine learning algorithm; and based on the identification model, identifying the quality of the musk sample to complete the identification of the quality of the musk. The method and the identification model are applied to quality identification of musk products with different qualities, quality identification of musk can be completed intelligently, efficiently and n</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNizEOwjAMRbMwIOAO5gBIVBVUHVEFgoUJ5sokbmqRuFFjBm5Phx6A6b8nvb80z5sohcCeRCF-8hvYTcgdW1QeBCJpPzh4YSYHk_ffRGNOZHXEABzRs3hAcYAphfm1NosOQ6bNvCuzvZwfzXVHaWgpJ7QkpG1zL4pDXVbHan8q_2l-QjY5-Q</recordid><startdate>20230407</startdate><enddate>20230407</enddate><creator>CHE LI</creator><creator>WANG YI</creator><creator>ZHAN ZHIXUE</creator><creator>HONG PENGXIONG</creator><creator>ZHONG YI</creator><creator>LAI ZHICHENG</creator><creator>LIAO GENJIE</creator><scope>EVB</scope></search><sort><creationdate>20230407</creationdate><title>Intelligent musk identification method based on hyperspectral imaging and application</title><author>CHE LI ; WANG YI ; ZHAN ZHIXUE ; HONG PENGXIONG ; ZHONG YI ; LAI ZHICHENG ; LIAO GENJIE</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN115937670A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2023</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>CHE LI</creatorcontrib><creatorcontrib>WANG YI</creatorcontrib><creatorcontrib>ZHAN ZHIXUE</creatorcontrib><creatorcontrib>HONG PENGXIONG</creatorcontrib><creatorcontrib>ZHONG YI</creatorcontrib><creatorcontrib>LAI ZHICHENG</creatorcontrib><creatorcontrib>LIAO GENJIE</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>CHE LI</au><au>WANG YI</au><au>ZHAN ZHIXUE</au><au>HONG PENGXIONG</au><au>ZHONG YI</au><au>LAI ZHICHENG</au><au>LIAO GENJIE</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Intelligent musk identification method based on hyperspectral imaging and application</title><date>2023-04-07</date><risdate>2023</risdate><abstract>The invention provides an intelligent musk identification method based on hyperspectral imaging and application, and relates to the field of traditional Chinese medicinal material identification, the identification method comprises the following steps: constructing a musk quality identification model: collecting hyperspectral data of a musk sample, obtaining a hyperspectral image, carrying out black and white correction processing, and intelligently selecting a region of interest by making a mask; calculating an average spectrum in the region of interest and carrying out spectrum preprocessing; constructing a musk identification model based on a machine learning algorithm; and based on the identification model, identifying the quality of the musk sample to complete the identification of the quality of the musk. The method and the identification model are applied to quality identification of musk products with different qualities, quality identification of musk can be completed intelligently, efficiently and n</abstract><oa>free_for_read</oa></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | |
ispartof | |
issn | |
language | chi ; eng |
recordid | cdi_epo_espacenet_CN115937670A |
source | esp@cenet |
subjects | CALCULATING COMPUTING COUNTING INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING PHYSICS TESTING |
title | Intelligent musk identification method based on hyperspectral imaging and application |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-04T00%3A51%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=CHE%20LI&rft.date=2023-04-07&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN115937670A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |