Paper Info
Title
An Improved Firefly Algorithm-Based 2-D Image Thresholding for Brain Image Fusion
Abstract
AbstractIn this article, an attempt is made to diagnose brain diseases like neoplastic, cerebrovascular, Alzheimer's, and sarcomas by the effective fusion of two images. The two images are fused in three steps. Step 1. Segmentation: The images are segmented on the basis of optimal thresholding, the thresholds are optimized with an improved firefly algorithm (pFA) by assuming Renyi entropy as an objective function. Earlier, image thresholding was performed with a 1-D histogram, but it has been recently observed that a 2-D histogram-based thresholding is better. Step 2: the segmented features are extracted with the scale invariant feature transform (SIFT) algorithm. The SIFT algorithm is good in extracting the features even after image rotation and scaling. Step 3: The fusion rules are made on the basis of an interval type-2 fuzzy set (IT2FL), where uncertainty effects are minimized unlike type-1. The novelty of the proposed work is tested on different benchmark image fusion data sets and has proven better in all measuring parameters.
Year
DOI
Venue
2020
10.4018/IJCINI.2020070104
Periodicals
Keywords
DocType
Volume
Firefly Algorithm, Image Fusion, Image Thresholding, Interval Type-2 Fuzzy, Renyi Entropy, Scale Invariant Feature Transform
Journal
14
Issue
ISSN
Citations 
3
1557-3958
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Srikanth M. V.100.34
V. V. K. D. V. Prasad200.34
K. Satya Prasad300.34