Vitality assessment of boar sperm using N Concentric Squares Resized (NCSR) texture descriptor in digital images

Enrique Alegre*, María Teresa García-Ordás, Víctor González-Castro, S. Karthikeyan

*Corresponding author for this work

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

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.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages540-547
Number of pages8
Volume6669 LNCS
DOIs
Publication statusPublished - 11 Jul 2011
Externally publishedYes
Event5th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2011 - Las Palmas de Gran Canaria, United Kingdom
Duration: 8 Jun 201110 Jun 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6669 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

Conference5th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2011
Country/TerritoryUnited Kingdom
CityLas Palmas de Gran Canaria
Period8/06/1110/06/11

Keywords

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

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