Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)

A New Method for Feature Extraction and Image Classification Based on PCNN and Image Quality

Authors
Yuan-zhi Liang, Rong Ma
Corresponding Author
Yuan-zhi Liang
Available Online December 2016.
DOI
10.2991/cnct-16.2017.77How to use a DOI?
Keywords
Feature Extraction, PCNN Model, Image Classification
Abstract

Considering that PCNN is in accordance with human vision, so it has a good performance in image binaryzation and segmentation, the PCNN-based methods have advantage in feature extraction and image classification. In this paper, we propose a new method for feature extraction and image classification based PCNN which is more robust than others. This method mainly analyzes the quality and centroid of the image and extracts features from the relationship between different centroid. Then, the Euclidean distance distribution parameters used to describe these features. In image classification, the feature parameter also play an important role and distinguishes the difference between various object images efficiently.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-301-2
ISSN
2352-538X
DOI
10.2991/cnct-16.2017.77How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yuan-zhi Liang
AU  - Rong Ma
PY  - 2016/12
DA  - 2016/12
TI  - A New Method for Feature Extraction and Image Classification Based on PCNN and Image Quality
BT  - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
PB  - Atlantis Press
SP  - 563
EP  - 570
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnct-16.2017.77
DO  - 10.2991/cnct-16.2017.77
ID  - Liang2016/12
ER  -