Feature Extraction Method for Wheat Diseases Based on Multi-fractal Spectrum

DOI

10.2991/iccsee.2013.765How to use a DOI?

Keywords

Wheat diseases, Multi-wavelet transform, Multi-fractal spectrum, Feature extraction, shape feature

Abstract

Wheat diseases image noise was effectively removed using lifting scheme multi-wavelet transform and multi-fractal analysis, and then it used multi-fractal theory to segment diseases image and extract eight multi-fractal spectrum values as wheat shape feature of diseases. Experiments showed that the shape characteristic value of different wheat diseases had great difference, and the shape characteristic value of similar diseases had certain regularity. Therefore, it could extract shape characteristic value to recognize wheat diseases.

Copyright

© 2013, 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  - Feiyun Zhang
PY  - 2013/03
DA  - 2013/03
TI  - Feature Extraction Method for Wheat Diseases Based on Multi-fractal Spectrum
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 3049
EP  - 3052
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.765
DO  - 10.2991/iccsee.2013.765
ID  - Zhang2013/03
ER  -