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Variable illumination compensation for pigskin leather images using local and global block analysis

Variable illumination seems to be a main challenge to any automatic image processing system particularly in the segmentation and recognition part. The new intensity variations, which do not presence in the original image, may lead to a false segmentation result. In this research, we present a method...

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Main Author: Azmi, Mohd Hafrizal
Format: Thesis
Language:English
Published: 2012
Online Access:http://psasir.upm.edu.my/id/eprint/38561/1/FK%202012%2023R.pdf
http://psasir.upm.edu.my/id/eprint/38561/
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spelling my.upm.eprints.385612015-05-05T04:35:15Z http://psasir.upm.edu.my/id/eprint/38561/ Variable illumination compensation for pigskin leather images using local and global block analysis Azmi, Mohd Hafrizal Variable illumination seems to be a main challenge to any automatic image processing system particularly in the segmentation and recognition part. The new intensity variations, which do not presence in the original image, may lead to a false segmentation result. In this research, we present a method to compensate the imbalance illumination in pigskin leather texture image. The main objective of this research is to offer an alternative pre-processing tool for further image enhancement procedures that is fast, simple and robust. The method utilizes the information within the local and global area of the image. The results are promising as the output image illumination condition is improved. In addition to that,the performances are either similar or better if to be compared to other established methods. However, the output images are affected by the visibility of the block boundaries. It happens due to the rapid intensity variation across the block boundaries, which is caused by the inaccurate residual selected for the normalization step. The next objective of this thesis is to remove the blockiness effect while still maintain the image attributes and improve the illumination condition. Some sets of modifications are employed to the basic model of local-global block analysis (B-LGBA) in order to eliminate the blockiness effect including horizontal improvement (HI-LGBA), vertical improvement (VI-LGBA), horizontal-vertical improvement (HVI-LGBA) and vertical-horizontal improvement (VHI-LGBA). The results produced by the enhanced LGBA illustrated that the modifications to be made are depending on the illumination trend. If the illumination is in one direction, the single modification is sufficient to remove all the boundaries. However, if the illumination is multi-directional, combined modifications are necessary, with the less-influencing direction must be dealt first. The accuracy of the proposed method is evaluated via the error of the numbers of the segmented region counted in the output image. Most of the outputs are oversegmented due to the existence of other low-intensity pixels which are contributed by the non-uniform surface of the sample and also the blocky pattern.From our 20 samples consist of different illumination types, the HVI -LGBA and VHI-LGBA yielded the lowest percentage of the errors with 29.52% and 35.43% compared to the errors produced by the B-LGBA which is equal to 120.35%. 2012 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/38561/1/FK%202012%2023R.pdf Azmi, Mohd Hafrizal (2012) Variable illumination compensation for pigskin leather images using local and global block analysis. Masters thesis, Universiti Putra Malaysia.
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Variable illumination seems to be a main challenge to any automatic image processing system particularly in the segmentation and recognition part. The new intensity variations, which do not presence in the original image, may lead to a false segmentation result. In this research, we present a method to compensate the imbalance illumination in pigskin leather texture image. The main objective of this research is to offer an alternative pre-processing tool for further image enhancement procedures that is fast, simple and robust. The method utilizes the information within the local and global area of the image. The results are promising as the output image illumination condition is improved. In addition to that,the performances are either similar or better if to be compared to other established methods. However, the output images are affected by the visibility of the block boundaries. It happens due to the rapid intensity variation across the block boundaries, which is caused by the inaccurate residual selected for the normalization step. The next objective of this thesis is to remove the blockiness effect while still maintain the image attributes and improve the illumination condition. Some sets of modifications are employed to the basic model of local-global block analysis (B-LGBA) in order to eliminate the blockiness effect including horizontal improvement (HI-LGBA), vertical improvement (VI-LGBA), horizontal-vertical improvement (HVI-LGBA) and vertical-horizontal improvement (VHI-LGBA). The results produced by the enhanced LGBA illustrated that the modifications to be made are depending on the illumination trend. If the illumination is in one direction, the single modification is sufficient to remove all the boundaries. However, if the illumination is multi-directional, combined modifications are necessary, with the less-influencing direction must be dealt first. The accuracy of the proposed method is evaluated via the error of the numbers of the segmented region counted in the output image. Most of the outputs are oversegmented due to the existence of other low-intensity pixels which are contributed by the non-uniform surface of the sample and also the blocky pattern.From our 20 samples consist of different illumination types, the HVI -LGBA and VHI-LGBA yielded the lowest percentage of the errors with 29.52% and 35.43% compared to the errors produced by the B-LGBA which is equal to 120.35%.
format Thesis
author Azmi, Mohd Hafrizal
spellingShingle Azmi, Mohd Hafrizal
Variable illumination compensation for pigskin leather images using local and global block analysis
author_facet Azmi, Mohd Hafrizal
author_sort Azmi, Mohd Hafrizal
title Variable illumination compensation for pigskin leather images using local and global block analysis
title_short Variable illumination compensation for pigskin leather images using local and global block analysis
title_full Variable illumination compensation for pigskin leather images using local and global block analysis
title_fullStr Variable illumination compensation for pigskin leather images using local and global block analysis
title_full_unstemmed Variable illumination compensation for pigskin leather images using local and global block analysis
title_sort variable illumination compensation for pigskin leather images using local and global block analysis
publishDate 2012
url http://psasir.upm.edu.my/id/eprint/38561/1/FK%202012%2023R.pdf
http://psasir.upm.edu.my/id/eprint/38561/
_version_ 1643832174000996352
score 13.211869

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