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» Modeling non-gaussian noise for robust image analysis
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ACIVS
2008
Springer
14 years 1 months ago
Robust Curvature Extrema Detection Based on New Numerical Derivation
Abstract. Extrema of curvature are useful key points for different image analysis tasks. Indeed, polygonal approximation or arc decomposition methods used often these points to ini...
Cédric Join, Salvatore Tabbone
CAIP
2009
Springer
171views Image Analysis» more  CAIP 2009»
13 years 11 months ago
Affine Moment Invariants of Color Images
A new type of affine moment invariants for color images is proposed in this paper. The traditional affine moment invariants can be computed on each color channel separately, yet wh...
Tomás Suk, Jan Flusser
IPMI
2005
Springer
14 years 1 months ago
PET Image Reconstruction: A Robust State Space Approach
Statistical iterative reconstruction algorithms have shown improved image quality over conventional nonstatistical methods in PET by using accurate system response models and measu...
Huafeng Liu, Yi Tian, Pengcheng Shi
ISTCS
1997
Springer
13 years 11 months ago
Learning with Queries Corrupted by Classification Noise
Kearns introduced the "statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this ...
Jeffrey C. Jackson, Eli Shamir, Clara Shwartzman
ICDAR
2009
IEEE
13 years 5 months ago
Document Image Binarisation Using Markov Field Model
This paper presents a new approach for the binarization of seriously degraded manuscript. We introduce a new technique based on a Markov Random Field (MRF) model of the document. ...
Thibault Lelore, Frédéric Bouchara