This paper proposes a new multi-level entropy-based image thresholding method. The key
principle of the proposed method depends on the minimum of the variance entropy. The …

Multilevel thresholding has been long considered as one of the most popular techniques for
image segmentation. Multilevel thresholding outputs a gray scale image in which more …

Thresholding is an important operation in image analysis which is used in many
applications. One of the most efficient techniques for image segmentation is the entropy …

Image thresholding is an important and efficient image segmentation technique, which is
crucial and essential for image analysis and computer vision. In this paper, we proposed a …

In the fields of computer vision and digital image processing, image segmentation denotes a
process whereby an image is segmented into multiple regions. Image segmentation based …

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 …

To improve the segmentation performance of thresholding methods, a novel strategy of
integrating the spatial information between pixel's is proposed in this paper. The proposed …

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 …

Over last few years, several methods have been proposed for image thresholding based on
entropy maximization. Some of these methods use gray level histogram, while others use …

An efficient hierarchical approach for image multi-level thresholding is proposed based on
the maximum entropy principle and Bayes' formula, in which no assumptions of the image …