Multilevel thresholding using Otsu or Kapur methods is widely used in the context of image
segmentation. These methods select optimal thresholds in gray level images by maximizing …

Image segmentation is widely used as a fundamental step for various image processing
applications. This paper focuses on improving the famous image thresholding method …

Abstract Background/Objectives: In this paper, Firefly Algorithm (FA) based multilevel
thresholding is proposed to segment the gray scale image by maximizing the entropy value …

The multilevel thresholding method with maximum entropy is one of the most important
image segmentation methods in image processing. However, its time-consuming …

Otsu reference proposed a criterion for maximizing the between-class variance of pixel
intensity to perform picture thresholding. However, Otsu's method for image segmentation is …

Thresholding is a commonly used technique for image segmentation. This paper presents
an efficient iterative algorithm for finding optimal thresholds that minimize a weighted sum-of …

For the image segmentation by the histogram bilevel thresholding, several methods have
been proposed. However, they are computationally time consuming and their effectiveness …

Image segmentation using multilevel thresholding (MT) is one of the leading methods.
Although, as most techniques are based on the image histogram to be segmented, MT …

Thresholding is a fundamental approach to segmentation that utilizes a significant degree of
pixel popularity or intensity. Otsu's thresholding employed the normalized histogram as a …

We introduce an alternative hybrid swarm algorithm for image segmentation that employs
multilevel thresholding techniques. For the hybridization, we have combined the whale …