Feature extraction of handwritten Kannada characters using curvelets and principal component analysis.
M. C. PadmaSaleem PashaPublished in: ICIP (2015)
Keyphrases
- principal component analysis
- feature extraction
- character recognition
- character segmentation
- optical character recognition
- text lines
- handwritten characters
- chinese characters
- dimensionality reduction
- linear discriminant analysis
- dimension reduction
- machine vision
- principal components
- handwriting recognition
- face recognition
- document images
- license plate
- word spotting
- printed documents
- discriminant analysis
- low dimensional
- feature space
- hand written
- preprocessing
- covariance matrix
- independent component analysis
- face images
- total variation
- image decomposition
- feature vectors
- document analysis
- writer independent
- handwritten text
- feature selection
- connected components
- neural classifier
- image processing
- kernel principal component analysis
- frequency domain
- fisher linear discriminant
- indian languages
- handwritten words
- wavelet transform
- feature set
- word recognition
- handwritten documents
- multiresolution
- fourier descriptors
- structural features
- language identification
- image fusion
- hough transform
- texture features
- image denoising
- curvelet transform
- high dimensional
- singular value decomposition
- complex background