Thresholding for weighted χ

A Percolation-based Thresholding Method with Applications in Functional Connectivity Analysis

Despite the recent advances in developing more effective thresholding methods to convert weighted networks to unweighted counterparts, there are still several limitations that need to be addressed. One such limitation is the inability of the most existing thresholding methods to take into account the topological properties of the original weighted networks during the binarization process, which...

Weighted Opposition-Based Fuzzy Thresholding

Unified formulation of a class of image thresholding techniques

-In this paper, we show that Otsu's image thresholding, Kittler and Illingworth's minimum error thresholding, and Huang and Wang's fuzzy thresholding methods can be derived under a similar mathematical formulation. The difference among the three methods is the choice of different weighting functions for computing a criterion function that can be considered as a weighted summation of the image g...

Unsupervised feature selection using weighted principal components

Feature selection has received considerable attention in various areas as a way to select informative features and to simplify the statistical model through dimensional reduction. One of the most widely used methods for dimensional reduction includes principal component analysis (PCA). Despite its popularity, PCA suffers from a lack of interpretability of the original feature because the reduce...

A Weighted Hybrid Thresholding Approach for Text Binarization

Text extraction in real images taken in unconstrained environments remains surprisingly challenging in Computer Vision due to language characteristics, complex backgrounds and the text color. Extraction of text and caption from images and videos is important and in great demand for video retrieval, annotation, indexing and content analysis. In this paper we propose a weighted hybrid thresholdin...