A novel algorithm is proposed for segmenting an image into multiple levels using its mean
and variance. Starting from the extreme pixel values at both ends of the histogram plot, the …

This paper proposes a new method of image thresholding by using cluster organization from
the histogram of an image. A new similarity measure proposed is based on inter-class …

Medical image processing is one of the real research regions in the most recent four
decades. Numerous researchers have contributed very great algorithms and reported …

This paper introduces the comparison of evolutionary and swarm-based optimization
algorithms for multilevel color image thresholding problem which is a process used for …

For the image segmentation by the histogram bilevel thresholding, several methods have
been proposed. However, they are computationally time consuming and their effectiveness …

Segmentation is an essential requirement in medicine when digital images are used in
illness diagnosis, especially, in posterior tasks as analysis and disease identification. An …

Nature-inspired algorithms emulate the mathematical and innovative techniques for non-
linear and real-life problems worldwide. Imaging technology is emerging out as one of the …

Most of the traditional histogram-based thresholding techniques are effective for bi-level
thresholding and unable to consider spatial contextual information of the image for selecting …

This paper presents a novel binarization algorithm for color document images. Conventional
thresholding methods do not produce satisfactory binarization results for documents with …

Multilevel thresholding techniques based on gray histogram are usually computationally
expensive for the image segmentation. In this paper, we propose a novel thresholding …