Comparing Hexagonal Image Resampling Techniques with Respect to Feature Extraction

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The hexagonal structure is considered to be preferable to the standard rectangular structure typically used for images in terms of the improved accuracy and efficiency that can be achieved for a number of image processing tasks. However, due to the lack of commercially available hexagonal image sensors, hexagonally structured images are generated by resampling from standard rectangular images and hence many resampling techniques exist for this purpose. Here we consider four such resampling techniques and apply recently developed scalable operators to them for the purpose of feature extraction. Each hexagonally structure image is evaluated with respect to feature extraction performance and we provide conclusions on the most accurate resampling technique currently available.
LanguageEnglish
Title of host publicationUnknown Host Publication
Pages102-115
Number of pages13
Publication statusPublished - 1 Jul 2011
Event14th International Machine Vision and Image Processing Conference - University of Limerick, Ireland
Duration: 1 Jul 2011 → …

Conference

Conference14th International Machine Vision and Image Processing Conference
Period1/07/11 → …

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Feature extraction
Image sensors
Image processing

Cite this

@inproceedings{412f61211bcd4c9599efa0063ee604ee,
title = "Comparing Hexagonal Image Resampling Techniques with Respect to Feature Extraction",
abstract = "The hexagonal structure is considered to be preferable to the standard rectangular structure typically used for images in terms of the improved accuracy and efficiency that can be achieved for a number of image processing tasks. However, due to the lack of commercially available hexagonal image sensors, hexagonally structured images are generated by resampling from standard rectangular images and hence many resampling techniques exist for this purpose. Here we consider four such resampling techniques and apply recently developed scalable operators to them for the purpose of feature extraction. Each hexagonally structure image is evaluated with respect to feature extraction performance and we provide conclusions on the most accurate resampling technique currently available.",
author = "Bryan Gardiner and SA Coleman and BW Scotney",
year = "2011",
month = "7",
day = "1",
language = "English",
isbn = "1-4438-2962-5",
pages = "102--115",
booktitle = "Unknown Host Publication",

}

Gardiner, B, Coleman, SA & Scotney, BW 2011, Comparing Hexagonal Image Resampling Techniques with Respect to Feature Extraction. in Unknown Host Publication. pp. 102-115, 14th International Machine Vision and Image Processing Conference, 1/07/11.

Comparing Hexagonal Image Resampling Techniques with Respect to Feature Extraction. / Gardiner, Bryan; Coleman, SA; Scotney, BW.

Unknown Host Publication. 2011. p. 102-115.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Comparing Hexagonal Image Resampling Techniques with Respect to Feature Extraction

AU - Gardiner, Bryan

AU - Coleman, SA

AU - Scotney, BW

PY - 2011/7/1

Y1 - 2011/7/1

N2 - The hexagonal structure is considered to be preferable to the standard rectangular structure typically used for images in terms of the improved accuracy and efficiency that can be achieved for a number of image processing tasks. However, due to the lack of commercially available hexagonal image sensors, hexagonally structured images are generated by resampling from standard rectangular images and hence many resampling techniques exist for this purpose. Here we consider four such resampling techniques and apply recently developed scalable operators to them for the purpose of feature extraction. Each hexagonally structure image is evaluated with respect to feature extraction performance and we provide conclusions on the most accurate resampling technique currently available.

AB - The hexagonal structure is considered to be preferable to the standard rectangular structure typically used for images in terms of the improved accuracy and efficiency that can be achieved for a number of image processing tasks. However, due to the lack of commercially available hexagonal image sensors, hexagonally structured images are generated by resampling from standard rectangular images and hence many resampling techniques exist for this purpose. Here we consider four such resampling techniques and apply recently developed scalable operators to them for the purpose of feature extraction. Each hexagonally structure image is evaluated with respect to feature extraction performance and we provide conclusions on the most accurate resampling technique currently available.

M3 - Conference contribution

SN - 1-4438-2962-5

SP - 102

EP - 115

BT - Unknown Host Publication

ER -