Detecting Maritime Obstacles Using Camera Images
نویسندگان
چکیده
Aqua farms will be the most frequently encountered obstacle when autonomous ships sail along coastal area of Korea. We used YOLOv5 to create a model that detects aquaculture buoys. The distances between buoys and camera were calculated based on monocular stereo vision using detected image coordinates compared with those from laser distance sensor radar. A dataset containing 2700 images was divided training testing data in ratio 8:2. trained had precision, recall, mAP 0.936%, 0.903%, 94.3%, respectively. Monocular calculates position estimation water surface maritime objects, while by finding corresponding points SSD, NCC, ORB then calculating disparity. small error rates ?3.16% ?14.81% for short (NCC) long (ORB); however, large errors objects located at far distance. 2.86% ?4.00% distances, is more effective than detecting obstacles can employed as auxiliary sailing equipment
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ژورنال
عنوان ژورنال: Journal of Marine Science and Engineering
سال: 2022
ISSN: ['2077-1312']
DOI: https://doi.org/10.3390/jmse10101528