Classification of boar spermatozoid head images using a model intracellular density distribution

Lidia Sánchez, Nicolai Petkov, Enrique Alegre

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)
212 Downloads (Pure)

Abstract

We propose a novel classification method to identify boar spermatozoid heads which present an intracellular intensity distribution similar to a model. From semen sample images, head images are isolated and normalized. We define a model intensity distribution averaging a set of head images assumed as normal by veterinary experts. Two training sets are also formed: one with images that are similar to the model and another with non-normal head images according to experts. Deviations from the model are computed for each set, obtaining low values for normal heads and higher values for heads assumed as non-normal. There is also an overlapping area. The decision criterion is determined to minimize the sum of the obtained false rejected and false acceptance errors. Experiments with a test set of normal and non-normal head images give a global error of 20.40%. The false rejection and the false acceptance rates are 13.68% and 6.72% respectively.
Original languageEnglish
Title of host publicationPROGRESS IN PATTERN RECOGNITION, IMAGE ANALYSIS AND APPLICATIONS, PROCEEDINGS
EditorsA Sanfeliu, ML Cortes
Place of PublicationBERLIN
PublisherSpringer
Pages154-160
Number of pages7
ISBN (Print)3-540-29850-9
Publication statusPublished - 2005
Event10th Iberoamerican Congress on Pattern Recognition - , Cuba
Duration: 15-Nov-200518-Nov-2005

Publication series

NameLECTURE NOTES IN COMPUTER SCIENCE
PublisherSPRINGER-VERLAG BERLIN
Volume3773
ISSN (Print)0302-9743

Other

Other10th Iberoamerican Congress on Pattern Recognition
CountryCuba
Period15/11/200518/11/2005

Keywords

  • MORPHOMETRY
  • SEMEN

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