Tilaiya reservoir catchment segmentation using hybrid soft cellular approach
Mahata, Kalyan ; Das, Rajib LU
and Sarkar, Anasua
LU
(2016)
3rd International Conference on Foundations and Frontiers in Computer, Communication and Electrical Engineering, C2E2 - 2016
p.281-288
- Abstract
Image segmentation among overlapping land cover areas in satellite images is a very crucial task. Detection of belongingness is the important problem for classifying mixed pixels. This paper proposes an approach for pixel classification using a hybrid approach of Fuzzy C-Means and Cellular automata methods. This new unsupervised method is able to detect clusters using 2-Dimensional Cellular Automata model based on fuzzy segmentations. This approach detects the overlapping regions in remote sensing images by uncertainties using fuzzy set membership values. As a discrete and dynamical system, cellular automaton explores the uniformly interconnected cells with states. In the second phase of our method, we utilize a 2-dimensional cellular... (More)
Image segmentation among overlapping land cover areas in satellite images is a very crucial task. Detection of belongingness is the important problem for classifying mixed pixels. This paper proposes an approach for pixel classification using a hybrid approach of Fuzzy C-Means and Cellular automata methods. This new unsupervised method is able to detect clusters using 2-Dimensional Cellular Automata model based on fuzzy segmentations. This approach detects the overlapping regions in remote sensing images by uncertainties using fuzzy set membership values. As a discrete and dynamical system, cellular automaton explores the uniformly interconnected cells with states. In the second phase of our method, we utilize a 2-dimensional cellular automaton to prioritize allocations of mixed pixels among overlapping land cover areas. We experiment our method on Tilaiya Reservoir Catchment on Barakar river for the first time. The clustered regions are compared with well-known FCM and K-Means methods and also with the ground truth knowledge. The results show the superiority of our new method.
(Less)
- author
- Mahata, Kalyan
; Das, Rajib
LU
and Sarkar, Anasua
LU
- publishing date
- 2016-01-01
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- host publication
- Foundations and Frontiers in Computer, Communication and Electrical Engineering - Proceedings of the 3rd International Conference on Foundations and Frontiers in Computer, Communication and Electrical Engineering, C2E2 - 2016
- editor
- Acharyya, Aritra
- pages
- 8 pages
- publisher
- CRC Press/Balkema
- conference name
- 3rd International Conference on Foundations and Frontiers in Computer, Communication and Electrical Engineering, C2E2 - 2016
- conference location
- Mankundu, India
- conference dates
- 2016-01-15 - 2016-01-16
- external identifiers
-
- scopus:85016220902
- ISBN
- 9781138028777
- language
- English
- LU publication?
- no
- id
- 010cab29-6b74-4886-8e68-376ed5479c7a
- date added to LUP
- 2018-10-09 09:45:00
- date last changed
- 2022-01-31 05:53:01
@inproceedings{010cab29-6b74-4886-8e68-376ed5479c7a,
abstract = {{<p>Image segmentation among overlapping land cover areas in satellite images is a very crucial task. Detection of belongingness is the important problem for classifying mixed pixels. This paper proposes an approach for pixel classification using a hybrid approach of Fuzzy C-Means and Cellular automata methods. This new unsupervised method is able to detect clusters using 2-Dimensional Cellular Automata model based on fuzzy segmentations. This approach detects the overlapping regions in remote sensing images by uncertainties using fuzzy set membership values. As a discrete and dynamical system, cellular automaton explores the uniformly interconnected cells with states. In the second phase of our method, we utilize a 2-dimensional cellular automaton to prioritize allocations of mixed pixels among overlapping land cover areas. We experiment our method on Tilaiya Reservoir Catchment on Barakar river for the first time. The clustered regions are compared with well-known FCM and K-Means methods and also with the ground truth knowledge. The results show the superiority of our new method.</p>}},
author = {{Mahata, Kalyan and Das, Rajib and Sarkar, Anasua}},
booktitle = {{Foundations and Frontiers in Computer, Communication and Electrical Engineering - Proceedings of the 3rd International Conference on Foundations and Frontiers in Computer, Communication and Electrical Engineering, C2E2 - 2016}},
editor = {{Acharyya, Aritra}},
isbn = {{9781138028777}},
language = {{eng}},
month = {{01}},
pages = {{281--288}},
publisher = {{CRC Press/Balkema}},
title = {{Tilaiya reservoir catchment segmentation using hybrid soft cellular approach}},
year = {{2016}},
}