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ICDAR
2003
IEEE
14 years 29 days ago
A Novel Feature Extraction Technique for the Recognition of Segmented Handwritten Characters
High accuracy character recognition techniques can provide useful information for segmentation-based handwritten word recognition systems. This research describes neural network-b...
Michael Blumenstein, Brijesh Verma, H. Basli
JMIV
2006
176views more  JMIV 2006»
13 years 7 months ago
Segmentation of Vectorial Image Features Using Shape Gradients and Information Measures
In this paper, we propose to focus on the segmentation of vectorial features (e.g. vector fields or color intensity) using region-based active contours. We search for a domain that...
Ariane Herbulot, Stéphanie Jehan-Besson, St...
WACV
2005
IEEE
14 years 1 months ago
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video
A number of recent systems for unsupervised featurebased learning of object models take advantage of cooccurrence: broadly, they search for clusters of discriminative features tha...
Thomas S. Stepleton, Tai Sing Lee
ICIP
1997
IEEE
14 years 9 months ago
Wavelet features for statistical object localization without segmentation
This paper describes a new technique for statistical 3{D object localization. Local feature vectors are extracted for all image positions, in contrast to segmentation in classical...
Heinrich Niemann, Josef Pösl
ICCV
2011
IEEE
12 years 7 months ago
Latent Low-Rank Representation for Subspace Segmentation and Feature Extraction
Low-Rank Representation (LRR) [16, 17] is an effective method for exploring the multiple subspace structures of data. Usually, the observed data matrix itself is chosen as the dic...
Guangcan Liu, Shuicheng Yan