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Image Segmentation Methods for Flood Monitoring System

By: Nur Atirah Muhadi, Ahmad Fikri Abdullah, Siti Khairunniza Bejo, Muhammad Razif Mahadi and Ana Mijic

Article Prepared By: Farah Izana Abdullah

 

Flood disasters are considered annual disasters in Malaysia and among the most dangerous disasters in the country. Lack of data during flood events is the main constraint to improving flood monitoring systems. In this era, computer vision approaches can be applied to improve flood detection and monitoring systems. Computer vision captures and processes images using segmentation techniques to understand their content. At present, there is no general solution to image segmentation problems that ensures reliable accuracy for flood disaster applications. Therefore, this study presents a comparative study of image segmentation techniques—namely thresholding, region growing, and a hybrid technique to extract water information from digital images. Hybrid technique was found to be the most promising image processing technique for extracting water features from digital images, with segmentation evaluation results higher than 95% on average.

Web: doi:10.3390/w12061825

 

Date of Input: 30/11/2021 | Updated: 30/11/2021 | nsyahirah

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INTERNATIONAL INSTITUTE OF AQUACULTURE AND AQUATIC SCIENCES
Universiti Putra Malaysia
43400 UPM Serdang
Selangor Darul Ehsan
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