Publications
2007
1.
González, Maribel; Alegre, Enrique; Alaiz-Rodríguez, Rocío; Sánchez-González, Lidia
Acrosome integrity classification of boar spermatozoon images using dwt and texture descriptors Artículo de revista
En: Computational Vision and Medical Image Processing: VipIMAGE, vol. 2007, 2007.
Resumen | Enlaces | BibTeX | Etiquetas: acrosome integrity, contour description, early fusion, fourier shape descriptor, LBP, SVM, texture description, wavelet
@article{gonzalez_acrosome_2007,
title = {Acrosome integrity classification of boar spermatozoon images using dwt and texture descriptors},
author = {Maribel González and Enrique Alegre and Rocío Alaiz-Rodríguez and Lidia Sánchez-González},
url = {https://d1wqtxts1xzle7.cloudfront.net/44449828/Acrosome_integrity_assessment_of_boar_sp20160405-3183-jdniiw-libre.pdf?1459894375=&response-content-disposition=inline%3B+filename%3DAcrosome_integrity_assessment_of_boar_sp.pdf&Expires=1738604441&Signature=gCki53PLr5Uqz1IsOZ87L788ljr1cPDhvd3XAIPiXXJyhy7gT1U0WIFjenpIGpKsNIg1lei0Y9wxLIssqiUqYYi2BrXDLX8qxHOSVnNjAj8bmBUVTWeiFHnHvMPbg–6ZzHG71Dj0RkarOCf1~C~OvGTQbjmSLusV5afdpSCJRuBd2eVbcFy4NGFcTSRMxPZGwJO-t87Aheo846zp-rUxOlkSN4YluJiuov6VhGnufaa4PfmwWgMSUxod9HGpYagpjvzk~RT24b73pZKITpgQqaeIrgE9O27~kYabvFZ3wWr8c0wEmGIBbj8doWz59ibPXF7GBaIzZXZj1TyWyvbQA__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA},
year = {2007},
date = {2007-01-01},
journal = {Computational Vision and Medical Image Processing: VipIMAGE},
volume = {2007},
abstract = {This study focuses on classifying boar sperm as acrosome-intact or acrosome-damaged using grayscale images from phase-contrast microscopy. By combining shape and texture descriptors with a Support Vector Machine (SVM), the authors achieve an F-Score of 0.9913, outperforming previous methods. This work highlights the importance of sperm head contour information and the effectiveness of early fusion techniques in sperm classification, making it a significant advancement in the field.},
keywords = {acrosome integrity, contour description, early fusion, fourier shape descriptor, LBP, SVM, texture description, wavelet},
pubstate = {published},
tppubtype = {article}
}
This study focuses on classifying boar sperm as acrosome-intact or acrosome-damaged using grayscale images from phase-contrast microscopy. By combining shape and texture descriptors with a Support Vector Machine (SVM), the authors achieve an F-Score of 0.9913, outperforming previous methods. This work highlights the importance of sperm head contour information and the effectiveness of early fusion techniques in sperm classification, making it a significant advancement in the field.