A
Project Report On
AUTOMATED RED BLOOD CELLS COUNT
Submitted By
OWAIS SHAIKH
MONIKA GUPTA
NEHARIKA BHAT
Under the guidance of
Prof. NARGIS SHAIKH
Submitted as a partial fulfillment of
Bachelor of Engineering
B.E. (Semester VIII),Computer Department
[2013 - 2014]
from
Rizvi College of Engineering
New Rizvi Educational Complex, Off-Carter Road,
Bandra(w), Mumbai - 400050
Affiliated to
University of Mumbai
CERTIFICATE
This is certify that the project report entitled
“AUTOMATED RED BLOOD CELLS COUNT”
Submitted By
OWAIS SHAIKH
MONIKA GUPTA
NEHARIKA BHAT
of Rizvi College of Engineering,Computer Department has been approved in partial fulfillment of re-
quirement for the degree of Bachelor of Engineering.
Prof. Nargis Shaikh Prof. ———————
Internal Guide External Guide (If any)
Prof. Dinesh B. Deore Dr. Varsha Shah
Head of Department Principal
Prof. ———————– Prof. ————————
Internal Examiner External Examiner
Date:
Acknowledgements
I am profoundly grateful to Prof. Nargis Shaikh for her expert guidance and continuous encouragement
throughout to see that this project rights its target.
I would like to express deepest appreciation towards Dr. Varsha Shah, Principal RCOE, Mumbai and
Prof. Dinesh B. Deore HOD Computer Department whose invaluable guidance supported me in this
project.
At last I must express my sincere heartfelt gratitude to all the staff members of Computer Engineering
Department who helped us directly or indirectly during this course of work.
OWAIS SHAIKH
MONIKA GUPTA
NEHARIKA BHAT
ABSTRACT
The deficiency of red blood cells, that constitutes 99 percent of blood cells and specialized as oxygen
carrier, causes various blood disorders.The estimation of RBC plays a crucial role in medical diagnosis
and pathological study. The main objective of this system is to detect and estimate the number of red
blood cells present in the blood smear sample image. The process is initiated by image acquisition and
image enhancement process. Noise removal from the blood smear image is the first step. This removes
the unwanted pixels from the image. Further the edges are preserved and binarization of the image is
performed, separating the region of interest from the background. Further the edges are preserved and
binarization of the image is performed. Then the task is to differentiate red blood cells from the various
other components in the blood by the segmentation process. Morphological operations are applied on
the blood image followed by RBC counting using Hough transform which is an efficient image segmen-
tation technique. The primary goal of the proposed system is to detect and count all the RBC including
the overlapping ones in the blood smear image.
Keywords : RBC, Image Processing, Pathalogy Operation
Contents
1 Introduction 1
1.1 Red Blood Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Blood diseases involving the Red Blood Cells . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Complete Blood Count . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Literature Survey 4
3 Proposed Work 7
3.1 Problem Definition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.2 Aims & Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3.3 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
4 Research Methodology 9
4.1 Existing System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
4.2 Drawbacks of Existing System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4.3 Feasibility Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4.3.1 Technical Feasibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
4.3.2 Economic Feasibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
5 Project Design 12
5.1 Hardware Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
5.2 Software Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
5.2.1 MATLAB: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
5.3 System Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
5.3.1 Image Acquisition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
5.3.2 Noise Removal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
5.3.3 Edge Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
5.3.4 Mathematical Morphological Operation . . . . . . . . . . . . . . . . . . . . . . 14
5.3.5 Red Blood Cell Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
5.3.6 Red Blood Cell Counting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
5.3.7 Hough Transform Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
5.4 RBC Count Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
5.5 Flowchart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
5.6 Use Case Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
