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001 9781315209203
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006 m o d
007 cr cnu|||unuuu
008 181126t20192019flu ob 001 0 eng d
040 _aOCoLC-P
_beng
_erda
_epn
_cOCoLC-P
020 _a9781351805940
_q(electronic bk.)
020 _a1351805940
_q(electronic bk.)
020 _a9781315209203
_q(electronic bk.)
020 _a1315209209
_q(electronic bk.)
020 _a9781351805957
020 _a1351805959
020 _a9781351805933
020 _a1351805932
020 _z9781138630796
035 _a(OCoLC)1076269166
_z(OCoLC)1070895154
_z(OCoLC)1077244600
035 _a(OCoLC-P)1076269166
050 4 _aTX547
072 7 _aTEC
_x012000
_2bisacsh
072 7 _aTDCT
_2bicssc
082 0 4 _a664.07
_223
245 0 0 _aHyperspectral imaging analysis and applications for food quality /
_cedited by N.C. Basantia, Leo M.L. Nollet, Mohammed Kamruzzaman.
264 1 _aBoca Raton, FL :
_bCRC Press, Taylor & Francis Group,
_c[2019]
264 4 _c©2019
300 _a1 online resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aFood analysis and properties
520 _aIn processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes. Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aHyperspectral imaging.
_912157
650 0 _aFood
_xAnalysis.
_913631
650 0 _aFood
_xQuality.
_917458
650 7 _aTECHNOLOGY & ENGINEERING
_xFood Science.
_2bisacsh
_98112
700 1 _aBasantia, N. C.,
_eeditor.
_917459
700 1 _aNollet, Leo M. L.,
_d1948-
_eeditor.
_917460
700 1 _aKamruzzaman, Mohammed,
_eeditor.
_917461
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781315209203
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 _cEBK
999 _c71532
_d71532