Multilevel thresholding for segmentation is an essential task and indispensable process in
various applications. Conventional color multilevel thresholding based image …

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 …

Multilevel thresholding is a simple and powerful image segmentation method that has
received widespread attention in recent years. However, the accuracy and stability of …

The objective of image segmentation is to extract meaningful objects. A meaningful
segmentation selects the proper threshold values to optimize a criterion using entropy. The …

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

Multilevel thresholding for image segmentation is a crucial process in several applications
such as feature extraction and pattern recognition. The meticulous search for the best values …

Multilevel thresholding has got more attention in the field of image segmentation recently.
However, it is still challenging and complicated for color image segmentation in many …

Optimal multilevel thresholding for image segmentation got much importance in recent
years. Several entropic and non-entropic objective functions with evolutionary computing …

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