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Noise resistant gradient calculation and edge detection using local binary patterns

: Teutsch, Michael; Beyerer, Jürgen

Volltext urn:nbn:de:0011-n-2387099 (1.9 MByte PDF)
MD5 Fingerprint: 0ee27e1f70529ac6dfebcdda8fc752fc
The original publication is available at
Erstellt am: 16.5.2013

Park, J.-I. (Ed.):
Computer Vision - ACCV 2012 Workshops : ACCV 2012 International Workshops, Daejeon, Korea, November 5-6, 2012, Revised Selected Papers, Part I
Berlin: Springer, 2013 (Lecture Notes in Computer Science 7728)
ISBN: 978-3-642-37409-8 (Print)
ISBN: 978-3-642-37410-4 (Online)
ISSN: 0302-9743
Asian Conference on Computer Vision (ACCV) <11, 2012, Daejeon>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Gradient calculation and edge detection are well-known problems in image processing and the fundament for many approaches for line detection, segmentation, contour extraction, or model fitting. A large variety of algorithms for edge detection already exists but strong image noise is still a challenge. Especially in automatic surveillance and reconnaissance applications with visual-optical, infrared, or SAR imagery, high distance to objects and weak signal-to-noise-ratio are difficult tasks to handle. In this paper, a new approach using Local Binary Patterns (LBPs) is presented, which is a crossover between texture analysis and edge detection. It shows similar results as the Canny edge detector under normal conditions but performs better in presence of noise. This characteristic is evaluated quantitatively with different artificially generated types and levels of noise in synthetic and natural images.