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

Entropy-based image thresholding are used widely in image processing. Conventional
methods are efficient in the case of bilevel thresholding. But they are very computationally …

Image segmentation using multilevel thresholding (MT) is one of the leading methods.
Although, as most techniques are based on the image histogram to be segmented, MT …

Image segmentation by thresholding is an important and fundamental task in image
processing and computer vision. In this paper, a new bi-level thresholding approach based …

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 …

Criterion based thresholding algorithms are simple and effective for two-level thresholding.
However, if a multilevel thresholding is needed, the computational complexity will …

In remote sensing imagery, segmentation techniques fail to encounter multiple regions of
interest due to challenges such as dense features, low illumination, uncertainties, and noise …

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

With rapid advancement of artificial intelligence via evolutionary optimization, multilevel
thresholding has become a feasible and critical way for image segmentation. Genetic …