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A Contrario Line Segment Detection
Barnes and Noble
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A Contrario Line Segment Detection in Chattanooga, TN
Current price: $54.99

Barnes and Noble
A Contrario Line Segment Detection in Chattanooga, TN
Current price: $54.99
Loading Inventory...
Size: Paperback
The reliable detection of low-level image structures is an old and still challenging problem in computer vision. 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 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.
a contrario
framework, the algorithm works efficiently without 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.
The reliable detection of low-level image structures is an old and still challenging problem in computer vision. 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 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.
a contrario
framework, the algorithm works efficiently without 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.

















