The objective of this paper is to propose an adaptive-evolutionary method for thresholding
which is used as an artificial intelligent algorithm for image segmentation especially for …

This paper presents a new method for thresholding using an evolutionary algorithm for
optimizing image threshold especially for object segmentation. This method is resistant …

Image Thresholding is one simplest method of image segmentation, which partitions the
image into several objects on the basis of one or more threshold values. Threshold values …

Thresholding is a popular image segmentation method that converts gray-level image into
binary image. The selection of optimum thresholds has remained a challenge over decades …

Image thresholding is a common segmentation technique with applications in various fields,
such as computer vision, pattern recognition, microscopy, remote sensing, and biology. The …

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

Image processing is largely used for gathering more knowledge/understanding either by
human or by machines like computer. Segmentation, Thresholding and Edge detection are …

Thresholding is a type of image segmentation, where the pixels change to make the image
easier to analyze. In bi-level thresholding, the image in grayscale format is transformed into …

One of the fundamental problems in image processing is image segmentation identifying the
objects and other structures in the image. Image thresholding is one of the widely used …

Thresholding is an important approach for image segmentation and it is the first step in the
image processing for many applications. Segmentation is a low level operation that can …