Segmentation of gray scale image based on intuitionistic fuzzy sets constructed from several membership functions
- 1 December 2014
- journal article
- Published by Elsevier BV in Pattern Recognition
- Vol. 47 (12), 3870-3880
- https://doi.org/10.1016/j.patcog.2014.07.003
Abstract
Segmentation is the process of extraction of objects from an image. This paper proposes a new algorithm to construct intuitionistic fuzzy set (IFS) from multiple fuzzy sets as an application to image segmentation. Hesitation degree in IFS is formulated as the degree of ignorance (due to the lack of knowledge) to determine whether the chosen membership function is best for image segmentation. By minimizing entropy of IFS generated from various fuzzy sets, an image is thresholded. Experimental results are provided to show the effectiveness of the proposed methodKeywords
This publication has 33 references indexed in Scilit:
- Hierarchical Remote Sensing Image Analysis via Graph Laplacian EnergyIEEE Geoscience and Remote Sensing Letters, 2012
- Image segmentation using Atanassov’s intuitionistic fuzzy setsExpert Systems with Applications, 2012
- Object Co-Segmentation Based on Shortest Path Algorithm and Saliency ModelIEEE Transactions on Multimedia, 2012
- Object cosegmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Ignorance functions. An application to the calculation of the threshold in prostate ultrasound imagesFuzzy Sets and Systems, 2010
- Yet Another Survey on Image Segmentation: Region and Boundary Information IntegrationLecture Notes in Computer Science, 2002
- Normalized cuts and image segmentationIeee Transactions On Pattern Analysis and Machine Intelligence, 2000
- A new method for gray-level picture thresholding using the entropy of the histogramComputer Vision, Graphics, and Image Processing, 1985
- Automatic grey level thresholding through index of fuzziness and entropyPattern Recognition Letters, 1983
- A Threshold Selection Method from Gray-Level HistogramsIEEE Transactions on Systems, Man, and Cybernetics, 1979