[cosc-grad-students-list] Thesis Defense - Sai Vinay Teja Manikonda

[Carrasco, Margo]

PRESENTER: Sai vinay teja Manikonda

TITLE: OIL SPILL DETECTION IN SAR IMAGES USING META-HEURISTIC SEARCH ALGORITHMS

DATE : 04/18/2018

TIME: 11:00AM - 12:00

LOCATION: CI 228

ABSTRACT:
In this research, two frameworks are introduced based on Meta-heuristic search algorithm to perform segmentation on Synthetic Aperture Radar (SAR) oil spill images, to detect the oil in the image and calculate the amount of oil spilled in that region.

The first one, a multilevel thresholding(MT) based on the Meta-heuristic search algorithm. The proposed algorithm encodes random samples from a feasible search space inside the image histogram as candidate solutions, whereas their quality is evaluated considering the objective functions that are employed by the OTSU methods. Guided by these objective values, the set of candidate solutions are evolved through the Meta-heuristic search algorithm operators until an optimal solution is found.

The second is, Segmentation of SAR images using cluster-based Meta-heuristic search algorithm. In this method we improve k means clustering algorithm by using Meta-heuristic search algorithm. Choosing good candidates for the initial centroid selection process for compact clustering algorithms, such as k-means, is essential for clustering quality and performance. Here a novel k means clustering algorithm using Meta-heuristic search algorithm is proposed. This model uses meta-heuristic methods to identify the good candidates for initial centroid selection in k-means clustering method.

Three Meta-heuristic search algorithm algorithms like, Genetic algorithm, Simulated Annealing, and Particle Swarm Optimization will be used in the frameworks to compare the results.


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