Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data

Snehlata; Neetu Mittal; Alexander Gelbukh

doi:10.1109/ICESC51422.2021.9532688

Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data

Snehlata, Neetu Mittal, Alexander Gelbukh

Centro de Investigación en Computación (CIC)

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

Edge detection is about identifying edges in an image. Edges identified in same spot images but captured at different time helps in understanding change detection. Finding the most suitable technique for edge detection is a thought-provoking and time-consuming task. This paper presents an implementation of genetic algorithm on 5 satellite images for edge detection. The proposed technique has been assessed with sobel and canny traditional techniques with the help of entropy values, and it was noted that GA method outperforms the sobel and canny techniques and produces an output image with better clarity and edges for change detection.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021
Editorial	Institute of Electrical and Electronics Engineers Inc.
Páginas	1372-1377
Número de páginas	6
ISBN (versión digital)	9781665428675
DOI	https://doi.org/10.1109/ICESC51422.2021.9532688
Estado	Publicada - 4 ago. 2021
Evento	2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021 - Coimbatore, India Duración: 4 ago. 2021 → 6 ago. 2021

Serie de la publicación

Nombre	Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021

Conferencia

Conferencia	2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021
País/Territorio	India
Ciudad	Coimbatore
Período	4/08/21 → 6/08/21

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10.1109/ICESC51422.2021.9532688

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Snehlata, Mittal, N., & Gelbukh, A. (2021). Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data. En Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021 (pp. 1372-1377). (Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICESC51422.2021.9532688

Snehlata ; Mittal, Neetu ; Gelbukh, Alexander. / Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data. Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 1372-1377 (Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021).

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title = "Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data",

abstract = "Edge detection is about identifying edges in an image. Edges identified in same spot images but captured at different time helps in understanding change detection. Finding the most suitable technique for edge detection is a thought-provoking and time-consuming task. This paper presents an implementation of genetic algorithm on 5 satellite images for edge detection. The proposed technique has been assessed with sobel and canny traditional techniques with the help of entropy values, and it was noted that GA method outperforms the sobel and canny techniques and produces an output image with better clarity and edges for change detection.",

keywords = "Artificial Intelligence, Change Detection, Edge Detection, Genetic Algorithm, Remote Sensed Data, Satellite Images, Segmentation",

author = "Snehlata and Neetu Mittal and Alexander Gelbukh",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021 ; Conference date: 04-08-2021 Through 06-08-2021",

year = "2021",

month = aug,

day = "4",

doi = "10.1109/ICESC51422.2021.9532688",

language = "Ingl{\'e}s",

series = "Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1372--1377",

booktitle = "Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021",

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Snehlata, Mittal, N & Gelbukh, A 2021, Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data. En Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021. Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021, Institute of Electrical and Electronics Engineers Inc., pp. 1372-1377, 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021, Coimbatore, India, 4/08/21. https://doi.org/10.1109/ICESC51422.2021.9532688

Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data. / Snehlata; Mittal, Neetu; Gelbukh, Alexander.
Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021. Institute of Electrical and Electronics Engineers Inc., 2021. p. 1372-1377 (Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data

AU - Snehlata,

AU - Mittal, Neetu

AU - Gelbukh, Alexander

PY - 2021/8/4

Y1 - 2021/8/4

N2 - Edge detection is about identifying edges in an image. Edges identified in same spot images but captured at different time helps in understanding change detection. Finding the most suitable technique for edge detection is a thought-provoking and time-consuming task. This paper presents an implementation of genetic algorithm on 5 satellite images for edge detection. The proposed technique has been assessed with sobel and canny traditional techniques with the help of entropy values, and it was noted that GA method outperforms the sobel and canny techniques and produces an output image with better clarity and edges for change detection.

AB - Edge detection is about identifying edges in an image. Edges identified in same spot images but captured at different time helps in understanding change detection. Finding the most suitable technique for edge detection is a thought-provoking and time-consuming task. This paper presents an implementation of genetic algorithm on 5 satellite images for edge detection. The proposed technique has been assessed with sobel and canny traditional techniques with the help of entropy values, and it was noted that GA method outperforms the sobel and canny techniques and produces an output image with better clarity and edges for change detection.

KW - Artificial Intelligence

KW - Change Detection

KW - Edge Detection

KW - Genetic Algorithm

KW - Remote Sensed Data

KW - Satellite Images

KW - Segmentation

UR - http://www.scopus.com/inward/record.url?scp=85116629022&partnerID=8YFLogxK

U2 - 10.1109/ICESC51422.2021.9532688

DO - 10.1109/ICESC51422.2021.9532688

M3 - Contribución a la conferencia

AN - SCOPUS:85116629022

T3 - Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021

SP - 1372

EP - 1377

BT - Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021

Y2 - 4 August 2021 through 6 August 2021

ER -

Snehlata, Mittal N, Gelbukh A. Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data. En Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 1372-1377. (Proceedings of the 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021). doi: 10.1109/ICESC51422.2021.9532688

Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data

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