Microfilariae Classification Using Multiple Classifiers for Color and Shape Features

Faroq AL-Tam, António Dos Anjos, Sébastien Pion, Michel Boussinesq, Hamid Reza Shahbazkia

Research output: Contribution to journalArticlepeer-review

1 Citation (SciVal)
129 Downloads (Pure)

Abstract

This paper presents a multi-classifier approach for classifying microfilariae in 2-D images. A shape descriptor based on the quench function is described. This descriptor is represented as a feature vector that encodes the shape information. The color feature vector is calculated as a histogram. Two classifiers were used to train both color and shape feature vectors, one for each vector. The posterior probabilities calculated from the scores of each classifier are then used to calculate the final classification decision. The experimental results show that, although the proposed approach is simple, it is efficient when compared to various approaches.

Original languageEnglish
Pages (from-to)560-565
Number of pages6
JournalOpen Engineering
Volume6
Issue number1
DOIs
Publication statusPublished - 05 Dec 2016

Keywords

  • illumination correction
  • Loa loa
  • loiasis
  • microfilariae
  • microscopy imaging
  • multi-classifier

Fingerprint

Dive into the research topics of 'Microfilariae Classification Using Multiple Classifiers for Color and Shape Features'. Together they form a unique fingerprint.

Cite this