Image segmentation is the technique in which an image into meaningful parts .It plays an important role in the image analysis and computer version. GA algorithm are evolutionary in nature so, it proved to be very time consuming. So, to overcome the limitation of the GA based on the multilevel thresholding, Ant Colony based Optimization on multilevel thresholding segmentation algorithm will be p...

Introduction: Nowadays virtual colonoscopy has become a reliable and efficient method of detecting primary stages of colon cancer such as polyp detection. One of the most important and crucial stages of virtual colonoscopy is colon segmentation because an incorrect segmentation may lead to a misdiagnosis.  Materials and Methods: In this work, a hybrid method based on Geometric Deformable Models...

Dry fingerprint has blurred image, because of overlapping of valleys, singular point to the fingertip and ridges. By using local entropy thresholding method, we extract the fingerprint images. This method is compared to canny filter images, sobel filter images and otsu algorithm images. This technique is used to enhance the contrast between valleys and ridges of the poor, medium and best image ...

The minimum cross entropy thresholding (MCET) has been widely applied in image processing. In this paper, a new multilevel MCET algorithm based on the artificial bee colony (ABC) algorithm is proposed. The proposed thresholding algorithm is called ABC-based MCET algorithm. Four different methods including the exhaustive search, the honey bee mating optimization (HBMO), the particle swarm optimi...

Background normalization algorithms attempt to suppress the ambient and self-noise during measurements of sonar, which enhance detection performance display effect weak signals. Conventional background methods are usually sensitive accuracy prior set filtering interval threshold, while significant noise is still detected in low frequency. In this paper, an improved algorithm proposed by thresho...

This paper proposes a global multi-level thresholding method for image segmentation. As a criterion for this, the traditional method uses the Shannon entropy, originated from information theory, considering the gray level image histogram as a probability distribution, while we applied the Tsallis entropy as a general information theory entropy formalism. For the algorithm, we used the artificia...

Image segmentation is a basic work in the field of image analysis and computer vision. Thresholding is one of the simplest methods of image segmentation. In general, thresholding approaches based on 1-D histogram do not make use of any space adjacent information of the image, thus it is often ruined by noise; thus, thresholding methods based on 2-D histogram are put forward. These methods have ...

Thresholding is one of the popular and fundamental techniques for conducting image segmentation. Many thresholding techniques have been proposed in the literature. Among them, the minimum cross entropy thresholding (MCET) have been widely adopted. Although the MCET method is effective in the bilevel thresholding case, it could be very time-consuming in the multilevel thresholding scenario for m...