Boar spermatozoa classification using longitudinal and transversal profiles (LTP) descriptor in digital images

Enrique Alegre*, Oscar García-Olalla, Víctor González-Castro, Swapna Joshi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A new textural descriptor, named Longitudinal and Transversal Profiles (LTP), has been proposed. This descriptor was used to classify 376 images of dead spermatozoa heads and 472 images of alive ones. The result obtained with this descriptor has been compared with the Pattern spectrum, Flusser, Hu, and a descriptor based on statistical values of the histogram. The features vectors computed have been classified using a back-propagation Neural Network and the kNN (k Nearest Neighbours) algorithm. Classification error obtained with LTP was 30.58% outperforming the other descriptors. The area under the ROC curve (AUC) has also been calculated confirming that the performance of the proposed descriptor is better that of the other texture descriptors.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages410-419
Number of pages10
Volume6636 LNCS
DOIs
Publication statusPublished - 2 Jun 2011
Externally publishedYes
Event14th International Workshop on Combinatorial Image Analysis, IWCIA 2011 - Madrid, United Kingdom
Duration: 23 May 201125 May 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6636 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference14th International Workshop on Combinatorial Image Analysis, IWCIA 2011
CountryUnited Kingdom
CityMadrid
Period23/05/1125/05/11

Keywords

  • boar semen assessment
  • classification
  • digital image analysis
  • texture descriptors

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