Thresholding plays an important role in image segmentation and image analysis. In this
paper, the normalized histogram of an image is fitted by a linear combined normal …

Thresholding is a popular image segmentation method that converts gray-level image into
binary image. The selection of optimum thresholds has remained a challenge over decades …

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) …

This chapter proposes a new method for determining the multilevel thresholding values for
image segmentation. The proposed method considers the multilevel threshold as multi …

Multilevel thresholding is the method applied to segment the given image into unique sub-
regions when the gray value distribution of the pixels is not distinct. The segmentation …

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 …

Image Segmentation is an open research area in which Multi-level thresholding is a topic of
current research. To automatically detect the threshold, histogram-based methods are …

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

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

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 …