texture image analysis is one of the most important working realms of imageprocessing in medical sciences and industry. up to present, different approacheshave been proposed for segmentation of texture images. in this paper, we offeredunsupervised texture image segmentation based on markov random field (mrf)model. first, we used gabor filter with different parameters’ (frequency,orientation) va...

Potato image segmentation is an important part of image-based potato defect detection. This paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on Genetic Algorithm (GA) optimization and morphological operators. The proposed potato color image segmentation is robust against variation of background, distance and ...

introduction this research addresses the automatic extraction of alluvial fans using four methods of segmentation from satellite data. this segmentation method divides images into partitions. it is typically used to recognize objects or other relevant purposes in digital images (fu, 2013:3260). alluvial fans have always been a landform that attracts human because they are suitable areas for liv...

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 novel algorithm based on genetic and regiona...

Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...

With the launch of very high spatial resolution sensors, a good positional quality can be expected from spatial imagery. Furthermore, efficient segmentation algorithms can increase the productivity and reduce the subjectivity of manual delineation. However, segmentation algorithms rely on a combination of parameters. This study used two indices to assess the quality of a segmentation in a fores...

background: accurate brain tissue segmentation from magnetic resonance (mr) images is an important step in analysis of cerebral images. there are software packages which are used for brain segmentation. these packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. thus, assessment of the quality of the segmented gray matter (gm), ...

Biometric recognition is an automatic identification method which is based on unique features or characteristics possessed by human beings and Iris recognition has proved itself as one of the most reliable biometric methods available owing to the accuracy provided by its unique epigenetic patterns. The main steps in any iris recognition system are image acquisition, iris segmentation, iris norm...