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

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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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  -