Linear feature delineation in digital imagery using neural networks

Persistent Link:
http://hdl.handle.net/10150/278012
Title:
Linear feature delineation in digital imagery using neural networks
Author:
Sementilli, Philip Joseph, Jr., 1958-
Issue Date:
1991
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 goal of many image analysis, image understanding and computer vision problems is the delineation of linear features. This thesis addresses the specific problem of operator guided road delineation in aerial photographs. Our solution to this problem applies the classical pattern recognition paradigm of feature extraction followed by pattern classification. The feature extraction process merges features extracted at different levels of a multi-resolution image pyramid to obtain a dichotomization of image coordinates into classes of road pixels and not road pixels. The road center line is estimated from this road pixel image using a generalized Hamming distance based decision scheme. An artificial neural network (ANN) architecture is developed which implements the generalized Hamming distance classifier. It is shown that the ANN implementation offers significant throughput improvements over sequential implementations. Results of applying the road delineation algorithm to digitized aerial photographs demonstrate delineation accuracy suitable for computer-aided cartography applications.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Geography.; Engineering, Electronics and Electrical.; Artificial Intelligence.; Computer Science.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College
Degree Grantor:
University of Arizona
Advisor:
Hunt, Bobby R.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleLinear feature delineation in digital imagery using neural networksen_US
dc.creatorSementilli, Philip Joseph, Jr., 1958-en_US
dc.contributor.authorSementilli, Philip Joseph, Jr., 1958-en_US
dc.date.issued1991en_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 goal of many image analysis, image understanding and computer vision problems is the delineation of linear features. This thesis addresses the specific problem of operator guided road delineation in aerial photographs. Our solution to this problem applies the classical pattern recognition paradigm of feature extraction followed by pattern classification. The feature extraction process merges features extracted at different levels of a multi-resolution image pyramid to obtain a dichotomization of image coordinates into classes of road pixels and not road pixels. The road center line is estimated from this road pixel image using a generalized Hamming distance based decision scheme. An artificial neural network (ANN) architecture is developed which implements the generalized Hamming distance classifier. It is shown that the ANN implementation offers significant throughput improvements over sequential implementations. Results of applying the road delineation algorithm to digitized aerial photographs demonstrate delineation accuracy suitable for computer-aided cartography applications.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectGeography.en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectArtificial Intelligence.en_US
dc.subjectComputer Science.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorHunt, Bobby R.en_US
dc.identifier.proquest1346430en_US
dc.identifier.bibrecord.b27227091en_US
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