Publications

@article{alegre_texture_2012,

title = {Texture and moments-based classification of the acrosome integrity of boar spermatozoa images},

author = {Enrique Alegre and Víctor González-Castro and Rocío Alaiz-Rodríguez and María Teresa García-Ordás},

url = {https://www.sciencedirect.com/science/article/pii/S0169260712000314},

year  = {2012},

date = {2012-01-01},

journal = {Computer Methods and Programs in Biomedicine},

volume = {108},

number = {2},

pages = {873–881},

abstract = {This paper addresses the automated assessment of sperm quality in the veterinary field by using image analysis to categorize boar spermatozoa acrosomes as intact or damaged. The acrosomes are characterized using texture features derived from first-order statistics, co-occurrence matrices, and Discrete Wavelet Transform coefficients. The study compares texture-based descriptors with moment-based ones and finds that texture descriptors outperform moment-based descriptors, achieving a classification accuracy of 94.93% using Multilayer Perceptron and k-Nearest Neighbors classifiers, offering a promising approach for veterinarians.},

note = {Publisher: Elsevier},

keywords = {acrosome integrity, boar semen, Discrete Wavelet Transform, Invariant Moments, k-Nearest Neigbours, neural networks, texture descriptors},

pubstate = {published},

tppubtype = {article}

}