Multilevel thresholding plays a significant role in the arena of image segmentation. The main
issue of multilevel image thresholding is to select the optimal combination of threshold value …

Image segmentation is imperative for image processing applications. Thresholding
technique is the easiest way of partitioning an image into different regions. Mostly, entropy …

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 …

At present, the research about fast algorithm for multi-threshold image segmentation is
mostly focused on bionic algorithm. Many of bionic algorithms, such as particle swarm …

Multilevel thresholding of images helps in separating the interesting objects from their
background. The quality of separation depends much on the selected threshold values. This …

Multilevel thresholding is one of the most important areas in the field of image segmentation.
However, the computational complexity of multilevel thresholding increases exponentially …

An automatic thresholding method based on Shannon entropy difference and dynamic
synergic entropy is proposed to select a reasonable threshold from the gray level image with …

Image segmentation refers to a procedure of segmenting the foreground (object of interest)
from the background. One of the well-known methods is thresholding based segmentation …

Multilevel thresholding technique is popular and extensively used in the field of image
processing. In this paper, a multilevel threshold selection is proposed based on edge …

Image segmentation is an important problem for image processing. The image processing
applications are generally affectedfromthe segmentation success. There is noany image …