A Contrario Line Segment Detection [electronic resource] / by Rafael Grompone von Gioi.

By:

Grompone von Gioi, Rafael [author.]

Contributor(s):

SpringerLink (Online service)

Material type: Text

TextSeries: SpringerBriefs in Computer SciencePublisher: New York, NY : Springer New York : Imprint: Springer, 2014Description: VIII, 90 p. 60 illus. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9781493905751

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

006.6 23

LOC classification:

T385
TA1637-1638
TK7882.P3

Online resources:

Click here to access online

Contents:

Introduction -- A Contrario Detection -- The LSD Algorithm -- Experiments -- Extensions.

In: Springer eBooksSummary: 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.

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
E-Book	Central Library		Available		E-40230

Introduction -- A Contrario Detection -- The LSD Algorithm -- Experiments -- Extensions.

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.

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