Detection of root knot nematodes in microscopy images

Faroq AL-Tam, António dos Anjos, Stephane Bellafiore, Hamid Reza Shahbazkia

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

2 Citations (Scopus)


Object detection in microscopy image is essential for further analysis in many applications. However, images are not always easy to analyze due to uneven illumination and noise. In addition, objects may appear merged together with debris. This work presents a method for detecting rice root knot nematodes in microscopy images. The problem involves four subproblems which are dealt with separately. The uneven illumination is corrected via polynomial fitting. The nematodes are then highlighted using mathematical morphology. A binary image is obtained and the microscope lines are removed. Finally, the detected nematodes are counted after thresholding the non-nematode particles. The results obtained from the performed tests show that this is a reliable and effective method when compared to manual counting.

Original languageEnglish
Title of host publicationBIOIMAGING 2015 - 2nd International Conference on Bioimaging, Proceedings; Part of 8th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2015
EditorsMario Forjaz Secca, Jan Schier, Ana Fred, Hugo Gamboa, Dirk Elias
Number of pages6
ISBN (Print)9789897580727, 9897580727
Publication statusPublished - 2015
Event2nd International Conference on Bioimaging, BIOIMAGING 2015 - Lisbon, Portugal
Duration: 12 Jan 201515 Jan 2015


Conference2nd International Conference on Bioimaging, BIOIMAGING 2015
Period12 Jan 201515 Jan 2015


  • Illumination correction
  • Mathematical morphology
  • Root knot nematodes
  • Thining
  • Vessel-like detection


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