Persistent Link:
http://hdl.handle.net/10150/277229
Title:
Multispectral analysis on a computer vision system
Author:
Yan, Bolin, 1954-
Issue Date:
1989
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
A procedure of multispectral analysis was developed to classify a two category image. The procedure utilized pattern recognition and feature extraction techniques. Images were acquired using a computer vision system with a series of interference filters to limit the wavelength band of the images. The procedure developed for multispectral analysis is: (1) Filter selection and image acquisition. (2) Pattern recognition. (3) Bayes minimum error rate classification. (4) Feature extraction by Fisher transformation or by Hotelling transformation. The analytical procedure was programmed in Microsoft C computer language and implemented on an IBM AT computer. The system was tested by identifying an apple against a Formica background. The classified images and histograms indicated that the separation was possible.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Spectrum analysis.; Robotics.; Computer vision.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College; Agricultural Engineering
Degree Grantor:
University of Arizona
Advisor:
Jondan, K. A.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleMultispectral analysis on a computer vision systemen_US
dc.creatorYan, Bolin, 1954-en_US
dc.contributor.authorYan, Bolin, 1954-en_US
dc.date.issued1989en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractA procedure of multispectral analysis was developed to classify a two category image. The procedure utilized pattern recognition and feature extraction techniques. Images were acquired using a computer vision system with a series of interference filters to limit the wavelength band of the images. The procedure developed for multispectral analysis is: (1) Filter selection and image acquisition. (2) Pattern recognition. (3) Bayes minimum error rate classification. (4) Feature extraction by Fisher transformation or by Hotelling transformation. The analytical procedure was programmed in Microsoft C computer language and implemented on an IBM AT computer. The system was tested by identifying an apple against a Formica background. The classified images and histograms indicated that the separation was possible.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectSpectrum analysis.en_US
dc.subjectRobotics.en_US
dc.subjectComputer vision.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineAgricultural Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorJondan, K. A.en_US
dc.identifier.proquest1339238en_US
dc.identifier.oclc24340661en_US
dc.identifier.bibrecord.b17853989en_US
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