Binary Gabor pattern (BGP) descriptor and principal component analysis (PCA) for steel surface defects classification.
Rachid ZaghdoudiHamid SeridiAdel boudiafSlimane ZianiPublished in: ICAASE (2020)
Keyphrases
- principal component analysis
- feature extraction
- fisher linear discriminant
- feature space
- dimension reduction
- face recognition
- surface defects
- principal components
- dimensionality reduction
- feature vectors
- independent component analysis
- linear discriminant analysis
- face images
- low dimensional
- dimensionality reduction methods
- covariance matrix
- kernel principal component analysis
- pattern recognition
- image classification
- discriminant analysis
- dimension reduction methods
- gabor wavelets
- face representation and recognition
- feature reduction
- neural classifier
- high dimensional
- local binary pattern
- lower dimensional
- principle component analysis
- computer vision
- principal components analysis
- texture classification
- machine vision
- image processing
- random projections
- training procedure
- linear discriminate analysis
- real time
- feature selection
- training set
- feature set
- fisher criterion
- support vector machine svm
- single image
- singular value decomposition
- gabor features
- kernel pca
- face databases
- gabor filters