A novel sea-land segmentation algorithm based on local binary patterns for ship detection

作者：Xia Yu; Wan Shouhong; Jin Peiquan; Yue Lihua

来源：International Journal of Signal Processing, Image Processing and Pattern Recognition, 2014, 7(3): 237-246.

DOI：10.14257/ijsip.2014.7.3.19

• Lbp features
• Local binary patterns
• Optical remote sensing
• Otsu method
• Sea-land segmentations
• Segmentation results
• Self adapting
• Ship detection

Ship detection is an important application of optical remote sensing image processing. Sea-land segmentation is the key step in ship detection. Traditional sea-land segment methods only based on the gray-level information of an image to choose a gray threshold to segment the image; however, it is very difficult to establish a self-adapting mechanism to select a suitable threshold for different images. Thus, the segmentation result is greatly influenced by the threshold chosen for sea-land segmentation. In this paper, we are integrating the LBP feature information to propose a novel sea-land segmentation algorithm. Moreover, a new ship detection method based on our sea-land segmentation algorithm is proposed for optical remote sensing images. The performance of ship detection is measured in terms of precision and false-alarm-rate. Experimental results show that, as compared to minimum error meth-od, the proposed algorithm can decrease the false-alarm-rate from 23.2% to 9.24%. And compared to Otsu method, the proposed algorithm improve the precision from 82.9% to 90.2%.

• 出版日期2014
• 单位中国科学技术大学