Titlebook: A Contrario Line Segment Detection; Rafael Grompone von Gioi Book 2014 The Author(s) 2014 A contrario framework.LSD algorithm.NFA approach

enormous

Beate Ochsner,Sybilla Nikolow,Robert StockThis chapter describes in full detail the LSD algorithm [31, 35, 36] for line segment detection. It is based on the . framework described in the previous chapter, but instead of searching exhaustively for line segments, it uses the . approach, resulting in an efficient algorithm. The source code and an online demo for LSD are available at [36].

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Erhard Schüttpelz,Beate Ochsner,Robert StockThis chapter presents some experiments to illustrate the behavior of the . line segment detector, indicating the good properties as well as its shortcomings. The results are compared with some existing approaches, concluding with an empirical evaluation of the algorithm computational time.

变态

Fleisch – Wandlung, Wachstum, ZüchtungThe motivation for this ambitious project was to provide a foundation for computer vision based, like the Gestalt theory [46, 51, 61, 62], on a small set of fundamental principles. They identified the lack of a principle to guide the selection of detection thresholds and their main contribution was

LASH

laxative

https://doi.org/10.1007/978-1-4939-0575-1A contrario framework; LSD algorithm; NFA approach; parameter tuning; parameterless

新娘

2191-5768 od and bad results are illustrated on real and synthetic images. The issues involved, as well as the strategies used, are common to many geometrical structure detection problems and some possible extensions are discussed.978-1-4939-0574-4978-1-4939-0575-1Series ISSN 2191-5768 Series E-ISSN 2191-5776

挣扎

Book 2014thout the need of any parameter tuning. The design criteria are thoroughly explained and the algorithm‘s good and bad results are illustrated on real and synthetic images. The issues involved, as well as the strategies used, are common to many geometrical structure detection problems and some possible extensions are discussed.

表皮

Foreknowledge

2191-5768 sion. This book leads a detailed tour through the LSD algorithm, a line segment detector designed to be fully automatic. Based on the .a contrario. framework, the algorithm works efficiently without the need of any parameter tuning. The design criteria are thoroughly explained and the algorithm‘s go

难听的声音

Fleisch – Wandlung, Wachstum, Züchtungset of fundamental principles. They identified the lack of a principle to guide the selection of detection thresholds and their main contribution was to propose the . framework to cover this need. This chapter will introduce the . approach and its application to line segment detection.