TOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION

Tomography is a technique for reconstructing an image of object cross-section using emitted waves. In this study, frequency selection and measurement systems for microwave tomography are proposed. Frequency selection is intended to determine the characteristics of microwave tomography using parallel...

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Main Author: Willyantho - NIM: 23215135 , Ricky
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/30435
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:30435
spelling id-itb.:304352018-10-01T10:01:22ZTOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION Willyantho - NIM: 23215135 , Ricky Indonesia Theses INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/30435 Tomography is a technique for reconstructing an image of object cross-section using emitted waves. In this study, frequency selection and measurement systems for microwave tomography are proposed. Frequency selection is intended to determine the characteristics of microwave tomography using parallel-beam projection. Perforated wood is used as a target that represents a hollow tree trunk. The microwave frequency used is 1.5 GHz, 3 GHz, and 4.5 GHz. The antenna used for measuring parallel-beam projections is a rectangular patch. Filtered back-projection, Algebraic Reconstruction Technique and back-propagation is used to reconstruct the image of parallel-beam projections. The results of this approach are evaluated for each frequency used. From the reconstruction image, a microwave frequency is chosen which can provide refractive index distribution information between wood and cavity more clearly. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Tomography is a technique for reconstructing an image of object cross-section using emitted waves. In this study, frequency selection and measurement systems for microwave tomography are proposed. Frequency selection is intended to determine the characteristics of microwave tomography using parallel-beam projection. Perforated wood is used as a target that represents a hollow tree trunk. The microwave frequency used is 1.5 GHz, 3 GHz, and 4.5 GHz. The antenna used for measuring parallel-beam projections is a rectangular patch. Filtered back-projection, Algebraic Reconstruction Technique and back-propagation is used to reconstruct the image of parallel-beam projections. The results of this approach are evaluated for each frequency used. From the reconstruction image, a microwave frequency is chosen which can provide refractive index distribution information between wood and cavity more clearly.
format Theses
author Willyantho - NIM: 23215135 , Ricky
spellingShingle Willyantho - NIM: 23215135 , Ricky
TOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION
author_facet Willyantho - NIM: 23215135 , Ricky
author_sort Willyantho - NIM: 23215135 , Ricky
title TOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION
title_short TOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION
title_full TOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION
title_fullStr TOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION
title_full_unstemmed TOMOGRAPHIC IMAGE RECONSTRUCTION USING PARALLEL-BEAM PROJECTION WITH MICROWAVE FREQUENCY FOR HOLLOW TREES DETECTION
title_sort tomographic image reconstruction using parallel-beam projection with microwave frequency for hollow trees detection
url https://digilib.itb.ac.id/gdl/view/30435
_version_ 1821995746267758592