| 한글제목(Korean Title) |
Adaptive Real-Time Ship Detection and Tracking Using Morphological Operations |
| 영문제목(English Title) |
Adaptive Real-Time Ship Detection and Tracking Using Morphological Operations |
| 저자(Author) |
Nasim Arshad
Kwang-Seok Moon
Jong-Nam Kim
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| 원문수록처(Citation) |
VOL 12 NO. 03 PP. 0168 ~ 0172 (2014. 09) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
In this paper, we propose an algorithm that can efficiently detect and monitor multiple ships in real-time. The proposed algorithm uses morphological operations and edge information for detecting and tracking ships. We used smoothing filter with a 3x3 Gaussian window and luminance component instead of RGB components in the captured image. Additionally, we applied Sobel operator for edge detection and a threshold for binary images. Finally, object labeling with connectivity and morphological operation with open and erosion were used for ship detection. Compared with conventional methods, the proposed method is meant to be used mainly in coastal surveillance systems and monitoring systems of harbors. A system based on this method was tested for both stationary and non-stationary backgrounds, and the results of the detection and tracking rates were more than 97% on average. Thousands of image frames and 20 different video sequences in both online and offline modes were tested, and an overall detection rate of 97.6% was achieved.
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| 키워드(Keyword) |
coastal surveillance
ship tracking
vessel identification
vessel tracking
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| 파일첨부 |
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