水准点(测量)
代表(政治)
计算机科学
线段
人工智能
直线(几何图形)
计算机视觉
模式识别(心理学)
图像(数学)
数字图像
目标检测
图像处理
数学
几何学
政治
政治学
大地测量学
法学
地理
作者
Nam Gyu Cho,Alan Yuille,Seong–Whan Lee
标识
DOI:10.1109/tpami.2017.2703841
摘要
This paper proposes a method for line segment detection in digital images. We propose a novel linelet-based representation to model intrinsic properties of line segments in rasterized image space. Based on this, line segment detection, validation, and aggregation frameworks are constructed. For a numerical evaluation on real images, we propose a new benchmark dataset of real images with annotated lines called YorkUrban-LineSegment. The results show that the proposed method outperforms state-of-the-art methods numerically and visually. To our best knowledge, this is the first report of numerical evaluation of line segment detection on real images.
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