Multi-level image thresholding is the most direct and effective method for image
segmentation, which is a key step for image analysis and computer vision, however, as the …

It is the most challenging and difficult task to segment a satellite image because of its
complete randomness, multiple regions of interest, weak correlation with pixels, and regions …

Satellite image segmentation is challenging due to the presence of weakly correlated and
ambiguous multiple regions of interest. Several bio-inspired algorithms were developed to …

Image processing is one of the major research regions in the most recent decades, in which,
image segmentation has gained more popularity due to its enormous applications. Before …

Multilevel thresholding has got more attention in recent years with various successful
applications. However, the implementation becomes more and more complex and time …

Color image segmentation is a vital preprocessing stage in various image processing
applications. In threshold-based segmentation, the success of the image segmentation …

In recent years, heuristic algorithms are extensively employed to offer optimal solutions for a
class of engineering optimization problems. In this paper, Otsu based bi-level and multi-level …

The drawback of the conventional multilevel thresholding methods is high computational
cost since they do exhaustive search among exponentialy growing number of possible …

This paper studied the multilevel threshold image segmentation-based metaheuristics
optimization methods and their applications. Image segmentation is a common problem in …

Multilevel thresholding is a fundamental, substantial and constructive technique that has
been widely recognized and concerned in recent years. However, the computational …