Segmentation of Sequences of Stereoscopic Images for Modelling Artificial Muscles

نویسندگان

  • Santiago González-Benítez
  • Rafael Verdú
  • Rafael Berenguer-Vidal
  • Pedro J. García-Laencina
چکیده

In this paper, an implementation of the Region Competition algorithm for segmenting stereoscopic video sequences is shown. This algorithm is an essential task in the method in order to obtain a 3D characterization of artificial muscles. Image sequences are acquired by a two-cam computer vision system. Optimal and efficient segmentation of these images is our goal; information obtained from the segmented first frame of the video sequence is used for segmenting the next frame and so on. Redundancy between stereoscopic pairs of images is also used to optimize the segmentation. In this paper, the Region Competition algorithm is described and our own specific implementation is addressed. Particular problems of stereoscopic video segmentation are shown and how they are solved. Finally, results yielded from simulations are presented and conclusions close the paper.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimized Region Competition Algorithm Applied to the Segmentation of Artificial Muscles in Stereoscopic Images

This paper addresses the implementation of the Region Competition algorithm for segmenting stereoscopic video sequences. The segmentation performed by this algorithm is an essential stage for the 3D characterization of artificial muscles. Image sequences are acquired by a two-cam computer vision system. The aim of this work is to come up with optimal and efficient segmentation of these images; ...

متن کامل

Efficient Unsupervised Content-Based Segmentation in Stereoscopic Video Sequences

This paper presents an e cient technique for unsupervised content-based segmentation in stereoscopic video sequences by appropriately combined di erent content descriptors in a hierarchical framework. Three main modules are involved in the proposed scheme; extraction of reliable depth information, image partition into color and depth regions and a constrained fusion algorithm of color segments ...

متن کامل

An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network

Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image arti...

متن کامل

Unsupervised Semantic Object Segmentation of Stereoscopic Video Sequences

In this paper, we present an efficient technique for unsupervised semantically meaningful object segmentation of stereoscopic video sequences. By this technique we achieve to extract semantic objects using the additional information a stereoscopic pair of frames provides. Each pair is analyzed and the disparity field, occluded areas and depth map are estimated. The key algorithm, which is appli...

متن کامل

A Method for Body Fat Composition Analysis in Abdominal Magnetic Resonance Images Via Self-Organizing Map Neural Network

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...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007