Detection of Texture Objects on Multichannel Images

A method for detecting extended texture objects on multi-channel images is proposed. The method is based on the representation of multi-digit digital images by a set of bit images and their approximation by three-dimensional Markov chains with two states. It is proposed to use transition probabiliti...

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Main Authors: ElenA Medvedeva, Alena Evdokimova
Format: Article
Language:English
Published: FRUCT 2019-04-01
Series:Proceedings of the XXth Conference of Open Innovations Association FRUCT
Subjects:
Online Access:https://fruct.org/publications/fruct24/files/Med.pdf
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author ElenA Medvedeva
Alena Evdokimova
author_facet ElenA Medvedeva
Alena Evdokimova
author_sort ElenA Medvedeva
collection DOAJ
description A method for detecting extended texture objects on multi-channel images is proposed. The method is based on the representation of multi-digit digital images by a set of bit images and their approximation by three-dimensional Markov chains with two states. It is proposed to use transition probabilities for three-dimensional Markov chains and brightness characteristics averaged within a sliding window as textural features. To reduce computational resources, determination of signs is carried out by the bit planes of the senior, most informative digits of the digital image. The detection of texture objects is based on the analysis of the histogram of the texture feature and the brightness of the pixels. The simulation results confirm the effectiveness of the proposed method.
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spelling doaj.art-669ab53b186748d4bc42344b2111382e2022-12-21T19:56:14ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372019-04-0185424249254Detection of Texture Objects on Multichannel ImagesElenA Medvedeva0Alena Evdokimova1Vyatka State University, VyatSU, Kirov, RussiaVyatka State University, VyatSU, Kirov, RussiaA method for detecting extended texture objects on multi-channel images is proposed. The method is based on the representation of multi-digit digital images by a set of bit images and their approximation by three-dimensional Markov chains with two states. It is proposed to use transition probabilities for three-dimensional Markov chains and brightness characteristics averaged within a sliding window as textural features. To reduce computational resources, determination of signs is carried out by the bit planes of the senior, most informative digits of the digital image. The detection of texture objects is based on the analysis of the histogram of the texture feature and the brightness of the pixels. The simulation results confirm the effectiveness of the proposed method.https://fruct.org/publications/fruct24/files/Med.pdf Markov multidimensional chainsDetecting texture objectsImage segmentation
spellingShingle ElenA Medvedeva
Alena Evdokimova
Detection of Texture Objects on Multichannel Images
Proceedings of the XXth Conference of Open Innovations Association FRUCT
Markov multidimensional chains
Detecting texture objects
Image segmentation
title Detection of Texture Objects on Multichannel Images
title_full Detection of Texture Objects on Multichannel Images
title_fullStr Detection of Texture Objects on Multichannel Images
title_full_unstemmed Detection of Texture Objects on Multichannel Images
title_short Detection of Texture Objects on Multichannel Images
title_sort detection of texture objects on multichannel images
topic Markov multidimensional chains
Detecting texture objects
Image segmentation
url https://fruct.org/publications/fruct24/files/Med.pdf
work_keys_str_mv AT elenamedvedeva detectionoftextureobjectsonmultichannelimages
AT alenaevdokimova detectionoftextureobjectsonmultichannelimages