One of the fundamental weaknesses of current computer vision systems used in outdoor applications is their inability to adapt the segmentation process as real-world changes occur in the image. We present a closed loop image segmentation system that incorporates a genetic algorithm to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions. ...

In this study, we propose a novel discrete-time coupled model to generate oscillatory responses via periodic points with a high periodic order. Our coupled system comprises one-dimensional oscillators based on the Rulkov map and a single globally coupled oscillator. Because the waveform of a one-dimensional oscillator has sharply defined peaks, the coupled system can be applied to dynamic image...

normal 0 false false false en-us x-none fa background:  regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. the method of segmentation is used to analyze anal to miscall structures in medical imaging. objective:  this study describes a new method for brain magnetic resonance image (mri) segmentation via a ...

Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...

Image segmentation algorithms allow the creation of variables that influence the attributes of the resulting objects. There is currently no set way of identifying the best segmentation parameters for a specific application. It would consequently be useful to calculate the accuracy of a particular segmentation for determining how well it can delineate an object of interest. This article assesses...

Unsupervised segmentation methods are important to extract boundary features from large forest vegetation databases. Finding optimized segmentation algorithms for images with natural vegetation is crucial because of the computational load and the required reproducibility of results. In this paper, we present an approach how to automatically select optimized parameter values for JSEG segmentatio...