Markov random field (MRF) theory has widely been applied to segmentation in noisy images. This paper proposes a new MRF method. First, it couples the original labeling MRF with a ...
We propose an original approach for the segmentation of three-dimensional fields of probability density functions. This presents a wide range of applications in medical images proc...
The paper deals with the design and implementation of a stereo algorithm. Disparity map is formulated as a Markov Random Field with a new smoothness constraint depending not only ...
Nello Balossino, Maurizio Lucenteforte, Luca Piova...
We present a new framework in which image segmentation, figure/ground organization, and object detection all appear as the result of solving a single grouping problem. This frame...
In this paper we show how a segmentation as preprocessing paradigm can be used to improve the efficiency and accuracy of model search in an image. We operationalize this idea usin...