Publications

@article{garcia-olalla_olivera_adaptive_2013,

title = {Adaptive local binary pattern with oriented standard deviation (ALBPS) for texture classification},

author = {Óscar García-Olalla Olivera and Enrique Alegre and Laura Fernández-Robles and María Teresa García-Ordás and Diego García-Ordás},

url = {https://link.springer.com/article/10.1186/1687-5281-2013-31},

year  = {2013},

date = {2013-01-01},

journal = {EURASIP journal on image and video processing},

volume = {2013},

pages = {1–11},

abstract = {This paper proposes a new texture description method combining local and global texture descriptors for image classification. The adaptive local binary pattern with oriented standard deviation (ALBPS) method provides enhanced local features, while the global description uses a wavelet transform-based descriptor, WCF13. These descriptors were combined with a support vector machine for classification, yielding high accuracy (85.63%) and F-score (0.886) for spermatozoa data and good results (84.45%) for the KTH-TIPS 2a dataset. The hybrid approach outperformed previous methods.},

note = {Publisher: Springer International Publishing},

keywords = {adaptive local binary pattern, hybrid feature extraction, image analysis, local binary pattern, spermatozoa assessment, support vector machine, texture classification, wavelet trasform},

pubstate = {published},

tppubtype = {article}

}