We introduce a very general method of achieving stable and fast color segmentation. This method works on diierent hierarchical data structures and combines local bottom-up region growing segmentation with top-down separation techniques. As our method supports exploitation of inherent parallelism, a real-time object detection has been designed and is in the implementation phase.

Introduction: Emotional stimulus is processed automatically in a bottom-up way or can be processed voluntarily in a top-down way. Imaging studies have indicated that bottom-up and top-down processing are mediated through different neural systems. However, temporal differentiation of top-down versus bottom-up processing of facial emotional expressions has remained to be clarified. The present st...

Pattern recognition is generally assumed as an interaction of two inversely directed image-processing streams: the bottom-up information details gathering and localization (segmentation) stream, and the top-down information features aggregation, association and interpretation (recognition) stream. Inspired by recent evidence from biological vision research and by the insights of Kolmogorov Comp...

We propose a Markov Random Field based image segmentation method which integrates domain specific information into MRF energy. The proposed segmentation method assumes that there is no labeled training set, but some priori general information referred as domain specific information about the dataset, is available. Domain specific information is received from a domain expert and formalized by a ...

use of nano-materials has increased in various aspects of human life. however, possible outbreak of nano-materials toxicity in humans and other organisms is one of the future challenges. different chemical precursors which are used in chemical approaches for production of nano-materials may have secondary and sometimes toxic effects in living organisms. these secondary effects may be reduced in...

Attentional Neural Network is a new framework that integrates top-down cognitive bias and bottom-up feature extraction in one coherent architecture. The top-down influence is especially effective when dealing with high noise or difficult segmentation problems. Our system is modular and extensible. It is also easy to train and cheap to run, and yet can accommodate complex behaviors. We obtain cl...

In this paper, we present a novel method for image segmentation of the hip joint structure. The key idea is to transfer the ground truth segmentation from the database to the test image. The ground truth segmentation of MR images is done by medical experts. The process includes the top down approach which register the shape of the test image globally and locally with the database of train image...

Image segmentation has long been an important problem in the computer vision community. In our recent work we have addressed the problem of texture segmentation, where we combined top-down and bottom-up views of the image into a unified procedure. In this paper we extend our work by proposing a modified procedure which makes use of graphs of image regions. In the topdown procedure a quadtree of...