Automatic classification of the acrosome status of boar spermatozoa using digital image processing and LVQ

E Alegre, M Biehl, N Petkov, L Sánchez - Computers in Biology and …, 2008‏ - Elsevier
We consider images of boar spermatozoa obtained with an optical phase-contrast
microscope. Our goal is to automatically classify single sperm cells as acrosome-intact …

Texture and moments-based classification of the acrosome integrity of boar spermatozoa images

E Alegre, V González-Castro, R Alaiz-Rodríguez… - Computer Methods and …, 2012‏ - Elsevier
The automated assessment of the sperm quality is an important challenge in the veterinary
field. In this paper, we explore how to describe the acrosomes of boar spermatozoa using …

Acrosome integrity assessment of boar spermatozoa images using an early fusion of texture and contour descriptors

O García-Olalla, E Alegre, L Fernández-Robles… - Computer methods and …, 2015‏ - Elsevier
The assessment of the state of the acrosome is a priority in artificial insemination centres
since it is one of the main causes of function loss. In this work, boar spermatozoa present in …

Statistical approach to boar semen evaluation using intracellular intensity distribution of head images

L Sánchez, N Petkov, E Alegre - Cellular and molecular biology, 2006‏ - research.rug.nl
We propose a method for the classification of boar sperm heads based on their intracellular
intensity distributions observed in microscopic images. The image pre-processing comprises …

Comparison of supervised and unsupervised methods to classify boar acrosomes using texture descriptors

E Alegre, V González-Castro… - 2009 International …, 2009‏ - ieeexplore.ieee.org
This work compares supervised and unsupervised techniques to classify images of boar
sperm heads according to their membrane integrity. We have used 5 different descriptors to …

[PDF][PDF] Acrosome integrity classification of boar spermatozoon images using dwt and texture descriptors

M González, E Alegre, R Alaiz… - … Vision and Medical …, 2007‏ - researchgate.net
Automatic assessment of boar sperm head images according to their acrosome status is a
challenge task in the veterinary field. In this paper we explore how much information texture …

LVQ acrosome integrity assessment of boar sperm cells

N Petkov, E Alegre, M Biehl… - … Modelling of Objects …, 2018‏ - taylorfrancis.com
We consider images of boar spermatozoa obtained with an optical phase-contrast
microscope. Our goal is to automatically classify single sperm cells as acrosome-intact …

Classification of boar sperm head images using learning vector quantization

M Biehl, P Pasma, M Pijl, L Sánchez… - … Symposium on Artificial …, 2006‏ - research.rug.nl
Abstract We apply Learning Vector Quantization (LVQ) in automated boar semen quality
assessment. The classification of single boar sperm heads into healthy (normal) and non …

Descripción adaptativa de texturas y estimación de las probabilidades a priori de las clases para el control de calidad seminal= Adaptive Texture Description and …

V González Castro - 2011‏ - buleria.unileon.es
En esta tesis se han evaluado varias técnicas para describir texturas en una imagen digital.
Además, hemos propuesto un nuevo método de segmentación inteligente, un descriptor de …

Estimation of boar sperm status using intracellular density distribution in grey level images

L Sánchez, N Petkov - Similarity-Based Clustering: Recent Developments …, 2009‏ - Springer
In this work we review three methods proposed to estimate the fraction of alive sperm cells in
boar semen samples. Images of semen samples are acquired, preprocessed and …