Counting of White blood cells (WBC) & characterizing their nucleus can provide valuable information to the doctors in order to identify different diseases or stage of a particular disease. The manual method is a tiresome process and has a lot of inaccuracy. On the other hand, the machine (hematological analyzer) based method are very expensive.
Digital image processing can be a less time consuming and cost effective method for counting and characterizing the WBC. In order to Count or characterize WBC by image processing, proper segmentation is the key challenge. In this paper we proposed an algorithm to segment WBC nucleus from microscopic images of stained peripheral blood film during leukemia and normal condition.
The proposed algorithm involves different steps such as color space conversion, color thresholding, filtering, marker controlled watershed and different morphological operations. The accuracy of the result obtained is 88.57%.
Keywords- White blood cells (WBC); segmentation; leukemi; morphological operatio; color space
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Software: Matlab 2020a or above
Hardware:
Operating Systems:
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is an Image/pixel?
· About image formats
· Introduction to Image Processing
· How digital image is formed
· Importing the image via image acquisition tools
· Analyzing and manipulation of image.
· Phases of image processing:
o Acquisition
o Image enhancement
o Image restoration
o Color image processing
o Image compression
o Morphological processing
o Segmentation etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills