Blood Cell Counting and Segmentation Using Image Processing Techniques

  • Ayesha Hoor Chaudhary
  • Javeria Ikhlaq
  • Muhammad Aksam Iftikhar
  • Maham Alvi
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)


The accurate count of a patient’s blood cells is vital for successful diagnosis of a plethora of diseases. Current systems deployed in Pakistan either rely on heavy and expensive machinery or is sometimes conducted manually. We propose the use of digital image processing techniques to build a cheaper alternative, that rely on digital images of blood smears, which are economical to produce, and are in fact a costless feature built-in to most existing lab microscopes. In this work, morphological image processing is deployed to segment the image and to differentiate and extract the blood cells from the plasma. The algorithm will exploit the shape and radius of blood cells for counting. After segmenting blood cells, their counting becomes a trivial task. The proposed system will be complementary to medical practitioners and provide a second opinion for their subjective diagnosis.


Complete blood count Segmentation Image processing Watershed Overlapping cells 


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ayesha Hoor Chaudhary
    • 1
  • Javeria Ikhlaq
    • 1
  • Muhammad Aksam Iftikhar
    • 1
  • Maham Alvi
    • 2
  1. 1.Department of Computer ScienceCOMSATS Institute of Information TechnologyLahorePakistan
  2. 2.Punjab University College of Information Technology, Quaid-e-Azam Campus, University of the PunjabLahorePakistan

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