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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.

Hollow thin walled NiO tubes functionalized by catalytic Pt were synthesized via nanofiber templating and multilayered sputter-coating of Pt and NiO thin overlayers followed by heat-treatment at 600 °C. Sandwich Pt-NiO-Pt tube networks exhibited superior C(2)H(5)OH sensing response and remarkable selectivity against CO and H(2) gases.

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