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» Novel image feature alphabets for object recognition
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ICPR
2008
IEEE
13 years 11 months ago
Novel image feature alphabets for object recognition
Most successful object recognition systems are based on a visual alphabet of quantised gradient orientations. Here, we introduce two richer image feature alphabets for use in obje...
Martin Lillholm, Lewis D. Griffin
CVPR
2006
IEEE
14 years 7 months ago
Incremental learning of object detectors using a visual shape alphabet
We address the problem of multiclass object detection. Our aims are to enable models for new categories to benefit from the detectors built previously for other categories, and fo...
Andreas Opelt, Axel Pinz, Andrew Zisserman
ICAPR
2005
Springer
13 years 10 months ago
A Novel Approach for Text Detection in Images Using Structural Features
We propose a novel approach for finding text in images by using ridges at several scales. A text string is modelled by a ridge at a coarse scale representing its center line and n...
H. Tran, Augustin Lux, H. L. Nguyen T, A. Boucher
BMCBI
2008
170views more  BMCBI 2008»
13 years 5 months ago
A genetic approach for building different alphabets for peptide and protein classification
Background: In this paper, it is proposed an optimization approach for producing reduced alphabets for peptide classification, using a Genetic Algorithm. The classification task i...
Loris Nanni, Alessandra Lumini
SCIA
2007
Springer
114views Image Analysis» more  SCIA 2007»
13 years 11 months ago
Object Recognition Using Frequency Domain Blur Invariant Features
In this paper, we propose novel blur invariant features for the recognition of objects in images. The features are computed either using the phase-only spectrum or bispectrum of th...
Ville Ojansivu, Janne Heikkilä