Autores
Gelbukh Alexander
Título Genetic Algorithm Implementation for Improved Change Detection on Remote Sensed Data
Tipo Congreso
Sub-tipo Memoria
Descripción 2nd International Conference on Electronics and Sustainable Communication Systems, ICESC 2021
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. © 2021 IEEE.
Observaciones DOI 10.1109/ICESC51422.2021.9532688
Lugar Coimbatore, Tamil Nadu
País India
No. de páginas 1372-1377
Vol. / Cap.
Inicio 2021-08-04
Fin 2021-08-06
ISBN/ISSN 9781665428675