loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ken'ichi Fujimoto ; Mio Musashi and Tetsuya Yoshinaga

Affiliation: The University of Tokushima, Japan

ISBN: 978-989-674-018-4

Keyword(s): Dynamic image segmentation, Coupled system, Chaotic neurons, Gray scale image, Multi-scaling of gray levels.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer Vision, Visualization and Computer Graphics ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Physiological Processes and Bio-Signal Modeling, Non-Linear Dynamics ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: In this paper, we describe an image segmentation technique for a gray scale image by utilizing the nonlinear dynamics of two respective discrete-time dynamical systems. The authors have proposed a discrete-time dynamical system that consists of a global inhibitor and chaotic neurons that can generate oscillatory responses. By utilizing oscillatory responses, our system can perform dynamic image segmentation, which denotes segmenting image regions in an image and concurrently exhibiting segmented images in time series, for a binary image. In order that our system can work for a gray scale image, we introduce a multi-scaling system as a pre-processing unit of our system. It is also made of a discrete-time dynamical system and can find an image region composed of pixels with different gray levels by multi-scaling gray levels of pixels. In addition, it can compute the proximity between pixels based on their multi-scaled gray levels. Computed proximity becomes significant information for d esigning parameters in our system. We demonstrated that our dynamic image segmentation system with the multi-scaling system works well for a gray scale image. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.228.24.192

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Fujimoto K.; Musashi M.; Yoshinaga T. and (2010). DYNAMIC IMAGE SEGMENTATION SYSTEM WITH MULTI-SCALING SYSTEM FOR GRAY SCALE IMAGE.In Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010) ISBN 978-989-674-018-4, pages 159-162. DOI: 10.5220/0002689701590162

@conference{biosignals10,
author={Ken'ichi Fujimoto and Mio Musashi and Tetsuya Yoshinaga},
title={DYNAMIC IMAGE SEGMENTATION SYSTEM WITH MULTI-SCALING SYSTEM FOR GRAY SCALE IMAGE},
booktitle={Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)},
year={2010},
pages={159-162},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002689701590162},
isbn={978-989-674-018-4},
}

TY - CONF

JO - Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)
TI - DYNAMIC IMAGE SEGMENTATION SYSTEM WITH MULTI-SCALING SYSTEM FOR GRAY SCALE IMAGE
SN - 978-989-674-018-4
AU - Fujimoto, K.
AU - Musashi, M.
AU - Yoshinaga, T.
PY - 2010
SP - 159
EP - 162
DO - 10.5220/0002689701590162

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.