Title: Medical image segmentation based on fuzzy 2-partition Kapur entropy using fast recursive algorithm

Authors: Ishpreet Singh Virk; Raman Maini

Addresses: Department of Computer Science and Engineering, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib-140407, Punjab, India ' Department of Computer Science and Engineering Punjabi University, Patiala-147002, Punjab, India

Abstract: Segmentation is a foremost part of computer-aided diagnosis (CAD) and medical image analysis. This paper provides an automatic threshold selection approach for the segmentation of medical images based on fuzzy 2-partition using Kapur entropy. The fuzzy 2-partition Kapur entropy approach converts the image into fuzzy 2-partition by applying two parameterised fuzzy membership functions. The optimal threshold is attained by searching for an ideal combination of the parameter for the fuzzy membership functions so that the fuzzy 2-partition Kapur entropy is maximised. The complexity of searching the optimal combination of parameters is reduced by integrating the concept of fast recursive algorithm and Kapur entropy. The proposed approach performance is measured using several medical images and it is found that results are considerable encouraging. The proposed approach could be put up as a component of a CAD system for early detection of diseases like cancer.

Keywords: fuzzy 2-partition; Kapur entropy; image thresholding; recursive algorithm; segmentation; fast recursive algorithm; fuzzy entropy; fuzzy membership function; recursive algorithm; medical image segmentation.

DOI: 10.1504/IJIEI.2020.112042

International Journal of Intelligent Engineering Informatics, 2020 Vol.8 No.4, pp.346 - 373

Received: 12 May 2020
Accepted: 26 Jul 2020
Published online: 23 Dec 2020 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article