Ship Detection Using Edge-Based Segmentation and Histogram of Oriented Gradient with Ship Size Ratio

• Published in: INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol. 15; no. 4; pp. 251 - 259
• Main Authors: Eum, Hyukmin, Bae, Jaeyun, Yoon, Changyong, Kim, Euntai
• Format: Journal Article
• Language: English
• Published: 한국지능시스템학회 30.12.2015
• Subjects: 전기공학; Histogram of oriented gradient; Edge-based segmentation; Ship detection; Support vector machine; Ship size ratio
• ISSN: 1598-2645; 2093-744X
• DOI: 10.5391/IJFIS.2015.15.4.251

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. KCI Citation Count: 3