Threshold selection is an important topic and also a critical preprocessing step for image
analysis, pattern recognition and computer vision. In this letter, a novel automatic image …

The conventional multilevel thresholding methods are computational expensive since they
exhaustively search the optimal thresholds to optimize the objective functions. In this paper …

In decades, Yang's cuckoo search algorithm has been widely developed to select the
optimal threshold of bi-level image threshoding, but the amount of computation of which …

Thresholding is an important technique for image segmentation that extracts a target from its
background on the basis of the distribution of gray levels. Many automatic threshold …

Automatic thresholding has been widely used in machine vision for automatic image
segmentation. Otsu's method selects an optimum threshold by maximizing the between …

In this paper, the multilevel thresholding method based on Kapur's entropy and the recently
proposed multi-swarm particle swarm optimization with a dynamic learning strategy is …

The conventional multilevel thresholding methods are inefficient in determining the optimal
thresholds due to the exponential growth in computation time. This paper a modified random …

In the area of image processing, segmentation of an image into multiple regions is very
important for classification and recognition steps. It has been widely used in many …

In a variety of image processing applications, multilevel thresholding image segmentation
has gotten a lot of interest. When traditional approaches are utilised, however, the process of …

Multi-level thresholding is one of the effective segmentation methods that have been applied
in many applications. Traditional methods face challenges in determining the suitable …