Automatic Segmentation of Malaria Affected Erythrocyte in Thin Blood Films

  • Komal B. RodeEmail author
  • Sangita D. Bharkad
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


In today’s world, a highly précised diagnostic method needs to be improved for management of feverish sickness and ensure that medicines are prescribed when necessary. The proposed algorithm is applied to giemsa-stained thin blood films. Using triangle’s thresholding technique, the erythrocytes are segmented, HSV color space based feature extraction is applied on the segmented erythrocytes. Features extracted are given to SVM classifier to identify whether the query sample is affected with a parasite or a normal sample. The performance of this algorithm is evaluated on the database collected from CDC website and 20 samples taken manually from a local hospital.


P. falciparum P. vivax Triangle’s thresholding SVM classifier RBC’s (erythrocytes) 



We are heartily grateful to the Medicare hospital, Ahmednagar for providing us the blood slides images which lead to the implementation of our project and some images were taken from the CDC website.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Electronics and TelecommunicationGovernment College of EngineeringAurangabadIndia

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