In this paper, we systematically review recent advances in surface inspection using
computer vision and image processing techniques, particularly those based on texture …

This paper presents a new, simple, and efficient segmentation approach, based on a fusion
procedure which aims at combining several segmentation maps associated to simpler …

We propose a Markov random field (MRF) image segmentation model, which aims at
combining color and texture features. The theoretical framework relies on Bayesian …

This monograph gives an introduction to the fundamentals of Markovian modeling in image
segmentation as well as a brief overview of recent advances in the field. Segmentation is …

This paper presents a novel segmentation approach based on a Markov random field (MRF)
fusion model which aims at combining several segmentation results associated with simpler …

Rice is one of the most widely cultivated food crops throughout the world. But due to
deficiency in the balance of mineral levels, the production of rice often gets severely …

In image processing, image segmentation is the process of partitioning a digital image into
multiple image segments. Among state‐of‐the‐art methods, Markov random fields can be …

This paper presents a new, simple and efficient segmentation approach, based on a fusion
procedure which aims at combining several segmentation maps associated to simpler …

Segment-based classification is one of the popular approaches for object detection, where
the performance of the classification task is sensitive to the accuracy of the output of the …

In this paper, we present a Hidden Markov Random Field (HMRF) data-fusion model. The
proposed model is applied to the segmentation of natural images based on the fusion of …