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Ship Detection Using Edge-Based Segmentation and Histogram of Oriented Gradient with Ship Size Ratio
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 Title & Authors
Ship Detection Using Edge-Based Segmentation and Histogram of Oriented Gradient with Ship Size Ratio
Eum, Hyukmin; Bae, Jaeyun; Yoon, Changyong; Kim, Euntai;
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In this paper, a ship detection method is proposed; this method uses edge-based segmentation and histogram of oriented gradient (HOG) with the ship size ratio. The proposed method can prevent a marine collision accident by detecting ships at close range. Furthermore, unlike radar, the method can detect ships that have small size and absorb radio waves because it involves the use of a vision-based system. This system performs three operations. First, the foreground is separated from the background and candidates are detected using Sobel edge detection and morphological operations in the edge-based segmentation part. Second, features are extracted by employing HOG descriptors with the ship size ratio from the detected candidate. Finally, a support vector machine (SVM) verifies whether the candidates are ships. The performance of these methods is demonstrated by comparing their results with the results of other segmentation methods using eight-fold cross validation for the experimental results.
Ship detection;Edge-based segmentation;Histogram of oriented gradient;Ship size ratio;Support vector machine;
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