Gaussian Membership Function and Type II Fuzzy Sets Based Approach for Edge Enhancement of Malaria Parasites in Microscopic Blood Images

  • Golla MadhuEmail author
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)


This research presents a three-stage approach. In the first stage, the original image transformed into grayscale image, then normalizes grayscale image using min-max normalization, which performs a linear conversion on the original image data. The second stage calculates the Gaussian membership function on the normalized grayscale image then measure lower membership values and upper membership values using a threshold value. In addition, computed a novel membership function with Hamacher t-conorm using lower and upper membership values on given images. Finally, the median filter applied on these images to obtain edge enhanced microscopic images. The current study is conducted on the microscopic blood images of the malaria parasites. The experimental results compared with Prewitt filter, Sobel edge filter, and rank-ordered filter. The proposed approach is consistent and coherent in all microscopic malaria parasite images with four stages, with average entropy 0.90215 and 59.69% PSNR values, respectively.


Edge enhancement Gaussian membership Interval type II fuzzy set Malaria parasite Microscopic images 



The author acknowledge DRDO-DRL, Tezpur, Assam, India for providing financial support to carry out this work (Task No. DRDO-DRLT-P1-2015/Task-64).


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Information TechnologyVNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadIndia

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