Multi-level thresholding is one of the most popular techniques in image segmentation.
However, selecting the optimal thresholds with high accuracy and efficiency is still …

Segmentation is a crucial step in image processing applications. This process separates
pixels of the image into multiple classes that permits the analysis of the objects contained in …

Traditional methods to address color image segmentation work efficiently for bi-level
thresholding. However, for multi-level thresholding, traditional methods suffer from time …

Today, image segmentation methods are widely used for various applications, including
object detection. Multilevel Thresholding Image Segmentation (MTIS) methods are among …

In this paper, a comprehensive energy function is used to formulate the three most popular
objective functions: Kapur's, Otsu and Tsalli's functions for performing effective multilevel …

Multilevel thresholding is a reliable and efficacious method for image segmentation that has
recently received widespread recognition. However, the computational complexity of the …

Image segmentation is a key stage in image processing because it simplifies the
representation of the image and facilitates subsequent analysis. The multi-level thresholding …

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

To improve the traditional image segmentation, an efficient multilevel thresholding
segmentation method based on improved Chimp Optimization Algorithm (IChOA) is …

Biologically inspired computing deals with complex real-world problems using elegantly
modeled techniques motivated by the behaviors of creatures in nature. Harris hawks …