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Image Processing Approaches and Disaster Management

Image Processing Approaches and Disaster Management

Surendra Rahamatkar
Copyright: © 2020 |Pages: 25
ISBN13: 9781799801825|ISBN10: 1799801829|ISBN13 Softcover: 9781799801832|EISBN13: 9781799801849
DOI: 10.4018/978-1-7998-0182-5.ch007
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MLA

Rahamatkar, Surendra. "Image Processing Approaches and Disaster Management." Challenges and Applications for Implementing Machine Learning in Computer Vision, edited by Ramgopal Kashyap and A.V. Senthil Kumar, IGI Global, 2020, pp. 163-187. https://doi.org/10.4018/978-1-7998-0182-5.ch007

APA

Rahamatkar, S. (2020). Image Processing Approaches and Disaster Management. In R. Kashyap & A. Kumar (Eds.), Challenges and Applications for Implementing Machine Learning in Computer Vision (pp. 163-187). IGI Global. https://doi.org/10.4018/978-1-7998-0182-5.ch007

Chicago

Rahamatkar, Surendra. "Image Processing Approaches and Disaster Management." In Challenges and Applications for Implementing Machine Learning in Computer Vision, edited by Ramgopal Kashyap and A.V. Senthil Kumar, 163-187. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-0182-5.ch007

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Abstract

This chapter presents the relevance of picture handling to distinguish different sorts of harm. For areal-type harm, 1) edge extraction, 2) unsupervised arrangement, 3) texture examination, and 4) edge improvement are suitable to distinguish harmed zone. For liner-type harm, it is hard to improve the permeability of harm partition by picture preparing. Likewise, the impact of overlaying office information to help staff to discover harm at an extraction is described.

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