Abstract
Two new textural descriptor, named N Concentric Squares Resized (NCSR) and N Concentric Squares Histogram (NCSH), have been proposed. These descriptors were used to classify 472 images of alive spermatozoa heads and 376 images of dead spermatozoa heads. The results obtained with these two novel descriptors have been compared with a number of classical descriptors such as Haralick, Pattern Spectrum, WSF, Zernike, Flusser and Hu. The feature vectors computed have been classified using kNN and a backpropagation Neural Network. The error rate obtained for NCSR with N = 11 was of 23.20% outperforms the rest of descriptors. Also, the area under the ROC curve (AUC) and the values observed in the ROC curve indicates the performance of the proposed descriptor is better than the others texture description methods.
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Alegre, E., García-Ordás, M.T., González-Castro, V., Karthikeyan, S. (2011). Vitality Assessment of Boar Sperm Using N Concentric Squares Resized (NCSR) Texture Descriptor in Digital Images. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_67
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DOI: https://doi.org/10.1007/978-3-642-21257-4_67
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