Search results for "Segmentation"

Video Indexing Using MPEG Motion Compensation Vectors

2003

In the last years a lot of work has been done on color, textural, structural and semantic indexing of "content-based" video databases. Motion-based video indexing has been less explored, with approaches generally based on the analysis of optical flows. Compressed videos require the decompression of the sequences and the computation of optical flows, two steps computationally heavy. In this paper we propose some methods to index videos by motion features (mainly related to camera motion) and by motion-based spatial segmentation of frames, in a fully automatic way. Our idea is to use MPEG motion vectors as an alternative to optical flows. Their extraction is very simple and fast; it doesn't r…

Video indexing using optical flow field

2002

The increasing development of advanced multimedia applications requires new technologies for organizing and retrieving by content databases of digital video. Several content based features (color, texture, motion, etc.) are needed to perform a reliable content based retrieval. We present a method for automatic motion based video indexing and retrieval. A prototypal system has been developed to prove the validity of our approach. Our system automatically splits a video into a sequence of shots, extracts a few representative frames (said r-frames) from each shot and computes some motion based features related to the optical flow field. Motion based queries are then performed either in a quali…

Morphological exponential entropy driven-HUM.

2006

This paper presents an improvement to the Ex- ponential Entropy Driven - Homomorphic Unsharp Masking (E 2 D − HUM ) algorithm devoted to illumination artifact sup- pression on Magnetic Resonance Images. E 2 D−HUM requires a segmentation step to remove dark regions in the foreground whose intensity is comparable with background, because strong edges produce streak artifacts on the tissues. This new version of the algorithm keeps the same good properties of E 2 D − HUM without a segmentation phase, whose parameters should be chosen in relation to the image. I. INTRODUCTION Most of the studies on illumination correction found in literature are oriented to brain (18) magnetic resonance images (…

Optic disc positioning and blood vessels extraction on eye fundus

2009

This paper presents two methods aimed to the optic disc positioning on the retinal images. The first is based on a template of the entire image, while the second is based on the retinal vascularisation. For this second task, also a vessel extraction method is provided. Both the algorithm have been tested on test images of the Drive Database.

Dealing with reconstruction problems: two cases study

Reconstruction problems are always included in a computer vision system as one of the key step toward the recognition of a scene. There are hierarchies of reconstruction that go from pixels to regions in the lower level, and from patches to objects in higher steps. The success of the reconstruction phase de-pends on several factors: the selection of "suitable" features, the matching function, the linking strategy. I this paper we show some of problems and solutions in two different contexts: the 3D reconstruction from cloud of points representing fragments of archeological finding, and the mosaicing from sea bed video frames. Preliminary results show that in both cases the accuracy is satis…

Image Segmentation through a Hierarchy of Minimum Spanning Trees

2012

Many approaches have been adopted to solve the problem of image segmentation. Among them a noticeable part is based on graph theory casting the pixels as nodes in a graph. This paper proposes an algorithm to select clusters in the images (corresponding to relevant segments in the image) corresponding to the areas induced in the images through the search of the Minimum Spanning Tree (MST). In particular is is based on a clustering algorithm that extracts clusters computing a hierarchy of Minimum Spanning Trees. The main drawback of this previous algorithm is that the dimension of the cluster is not predictable and a relevant portion of found clusters can be composed by micro-clusters that ar…

Entropy-based Localization of Textured Regions

2011

Appearance description is a relevant field in computer vision that enables object recognition in domains as re-identification, retrieval and classification. Important cues to describe appearance are colors and textures. However, in real cases, texture detection is challenging due to occlusions and to deformations of the clothing while person's pose changes. Moreover, in some cases, the processed images have a low resolution and methods at the state of the art for texture analysis are not appropriate. In this paper, we deal with the problem of localizing real textures for clothing description purposes, such as stripes and/or complex patterns. Our method uses the entropy of primitive distribu…

Exponential Entropy Driven HUM on Knee MR Images

2007

A very important artifact corrupting Magnetic Resonance Images is the RF inhomogeneity. This kind of artifact generates variations of illumination which trouble both direct examination by the doctor and segmentation algorithms. Even if homomorphic filtering approaches have been presented in literature, none of them has developed a measure to determine the cut-off frequency. In this work we present a measure based on information theory with a large experimental setup aimed to demonstrate the validity of our approach.

Automatic Volumetric Liver Segmentation Using Texture Based Region Growing

2010

In this paper an automatic texture based volumetric region growing method for liver segmentation is proposed. 3D seeded region growing is based on texture features with the automatic selection of the seed voxel inside the liver organ and the automatic threshold value computation for the region growing stop condition. Co-occurrence 3D texture features are extracted from CT abdominal volumes and the seeded region growing algorithm is based on statistics in the features space. Each CT volume is composed by 230 slices, having 512 x 512 pixels as spatial resolution, and 12-bit gray level resolution. In this initial feasible study, 5 healthy volunteer acquisitions has been used. Tests have been p…

A Graph-Based Method for PET Image Segmentation in Radiotherapy Planning: A Pilot Study

2013

Target volume delineation of Positron Emission Tomography (PET) images in radiation treatment planning is challenging because of the low spatial resolution and high noise level in PET data. The aim of this work is the devel- opment of an accurate and fast method for semi-automatic segmentation of me- tabolic regions on PET images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Va- lidation was first performed on phantoms containing spheres and irregular in- serts of different and known volumes, then tumors from a patient with head and neck cancer were segmented to discuss the clinical applicability of this algo- rith…