Informace o publikaci

RSurf Texture Descriptor

Logo poskytovatele
Název česky Popisovač textúry RSurf
Autoři

MAJTNER Tomáš STOKLASA Roman SVOBODA David

Rok publikování 2014
Druh Software
Fakulta / Pracoviště MU

Fakulta informatiky

www http://cbia.fi.muni.cz/projects/rsurf-texture-descriptor.html
Popis In biomedical image analysis, object description and classification tasks are very common. Our work relates to the problem of classification of Human Epithelial (HEp-2) cells. Since the crucial part of each classification process is the feature extraction and selection, much attention should be concentrated to the development of proper image descriptors. In this article, we introduce a new efficient texture-based image descriptor for HEp-2 images. We compare proposed descriptor with LBP, Haralick features (GLCM statistics) and Tamura features using the public MIVIA HEp-2 Images Dataset. Our descriptor outperforms all previously mentioned approaches and the kNN classifier based solely on the proposed descriptor achieve the accuracy as high as 91.1%.
Související projekty:

Používáte starou verzi internetového prohlížeče. Doporučujeme aktualizovat Váš prohlížeč na nejnovější verzi.

Další info