The conventional multilevel thresholding methods are efficient for bi-level thresholding.
However, they are computationally expensive extending to multilevel thresholding since …

Multilevel thresholding image segmentation is an important technique, which has attracted
much attention in recent years. The conventional exhaustive search method for image …

Segmentation is a critical task in image processing. Bi-level segmentation involves dividing
the whole image into partitions based on a threshold value, whereas multilevel …

Previous optimal thresholding methods are popular and efficient in the case of bi-level
thresholding but are computationally expensive when extended to multilevel thresholding to …

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 …

In this paper, a hybrid approach, which is based on Gaussian smoothing and a genetic
algorithm (GA), is proposed for automatic multilevel image thresholding. Using a mixture …

Multilevel thresholding is one of the most popular approaches used for image segmentation.
Several methods have been used to find the threshold values; however, metaheuristic (MH) …

Multilevel thresholding is a very important image processing technique in the field of image
segmentation. However, the computational complexity of determining the optimal threshold …

A metaheuristic algorithm called Harris hawks optimization (HHO) is gaining its popularity
among its clan and useful for optimization. In this algorithm, the prey gets completely …

A new method of thresholding a gray-scale image into a desired number of classes is
proposed in this paper. The proposed method first evaluates the number of peaks in the …