Remotely sensed images usually require segmentation in presence of uncertainty, because
of factors like environmental conditions, poor resolution and poor illumination. Therefore, to …

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

Multilevel thresholding is one of the most widely used techniques for image segmentation.
However, the conventional multilevel thresholding methods are time-consuming algorithms …

Multilevel thresholding has important research value in image segmentation and can
effectively solve region analysis problems of complex images. In this paper, Otsu and …

Image segmentation is a critical step in digital image processing applications. One of the
most preferred methods for image segmentation is multilevel thresholding, in which a set of …

Multilevel thresholding is one of the most broadly used approaches to image segmentation.
However, the traditional techniques of multilevel thresholding are time-consuming …

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 is a method that is widely used in image segmentation. The
thresholding problem is treated as an optimization problem with an objective function. In this …

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 …

Multilevel thresholding is one of the most popular image segmentation techniques. In order
to determine the thresholds, most methods use the histogram of the image. This paper …