Volume 12, Issue 4, April 2020

 

 

Fuzzy Image Processing Based Architecture for Contrast Enhancement in Diabetic Retinopathy Images
 

Fuzzy Image Processing Based Architecture for Contrast Enhancement in Diabetic Retinopathy Images

Pages: 26-30 (5) | [Full Text] PDF (729 KB)
BMK Younis, DB Younis
Department of Computer Technology Engineering, Engineering Technical College, Northern Technical University Mosul, Iraq

https://doi.org/10.47277/IJCEIT/12(4)1


Abstract -
Diabetic retinopathyā€¯ is damage to retina denotes one of the problems of diabetes which is a significant reason for visual infirmity and blindness. A comprehensive and routine eye check is important to early detection and rapid treatment. This study proposes a hardware system that can enhance the contrast in the diabetic retinopathy eye fundus images as a first step in different eye disease diagnoses. The fuzzy histogram equalization technique is proposed to increases the local contrast of Diabetic Retinopathy Images. First, a histogram construction hardware architecture for different image processing purposes has been built then modified with fuzzy techniques to create fuzzy histogram equalization architecture, which is used to enhance the original images. Both architectures are designed using a finite-state machine (FSM) technique and programmed with VHDL programming language. The first one is implemented using two (Spartan 3E-XC3S500 and Xilinx Artix-7 XC7A100T) kits, while the second architecture is implemented using (Spartan 3E-XC3S500) kit. The system consists also of a modified video graphics array (VGA) port to display the input and resulted images with a proper resolution. All the hardware outputs are compared to that results produce from MatLab for verification and the resulted images are tested by PSNR, MSE, ENTROPY ,and AMBE.
 
Index Terms - Histogram Equlization, Fuzzy, contrast enhancement, Diabetic Retinopathy, FPGA

Citation - BMK Younis, DB Younis. "Fuzzy Image Processing Based Architecture for Contrast Enhancement in Diabetic Retinopathy Images." International Journal of Computer Engineering and Information Technology 12, no. 4 (2020): 26-30.