Combining the contrast information with LPQ for texture classification
- 1 March 2012
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2012 6th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)
Abstract
Texture classification is an important problem in image analysis. A considerable amount of research work has been done for local or global rotation invariant feature extraction for texture classification. Local invariant features contain the spatial information, but usually do not have the contrast information. A new hybrid approach is proposed which considers the contrast information in spatial domain and the phase information in frequency domain of the image. It uses the joint histogram of the two complementary features, local phase quantization (LPQ) and the contrast of the image. Support vector machine is used for classification. The experimental results on standard benchmark datasets for texture classification Brodatz and KTH-TIPS2-a show that the proposed method can achieve significant improvement compared to the LPQ, Gabor filer or local Binary Pattern methods.Keywords
This publication has 20 references indexed in Scilit:
- Rotation invariant texture classification using LBP variance (LBPV) with global matchingPattern Recognition, 2010
- Texture classification and segmentation using wavelet packet frame and Gaussian mixture modelPattern Recognition, 2007
- Multiresolution gray-scale and rotation invariant texture classification with local binary patternsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
- Texture analysis for classification of cervix lesionsIEEE Transactions on Medical Imaging, 2000
- Digital image restorationIEEE Signal Processing Magazine, 1997
- Texture features for browsing and retrieval of image dataIEEE Transactions on Pattern Analysis and Machine Intelligence, 1996
- Texture classification and segmentation using wavelet framesIEEE Transactions on Image Processing, 1995
- Evaluation of textural and multipolarization radar features for crop classificationIEEE Transactions on Geoscience and Remote Sensing, 1995
- Texture classification by wavelet packet signaturesIEEE Transactions on Pattern Analysis and Machine Intelligence, 1993
- Automated inspection of textile fabrics using textural modelsIEEE Transactions on Pattern Analysis and Machine Intelligence, 1991