Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering

Analysis of DNA molecular genetics features in infected styphnolobium japonicum

Authors
Zhongyi Hu
Corresponding Author
Zhongyi Hu
Available Online April 2015.
DOI
https://doi.org/10.2991/amcce-15.2015.222How to use a DOI?
Keywords
DNA image; infected styphnolobium japonicum; identification rate
Abstract
During the study of DNA image recognition at the beginning of infected styphnolobium japonicum, the features of DNA profile are arbitrary. Both characteristic angle and direction change are disorderedly distributed. This study presents a new method to examine the features of early DNA profile based on gray-level co-occurrence matrix (GLCM) and fuzzy mean clustering. Different types of lesion characteristics are distinguished by learning sets and fuzzy means clustering methods. Multilayer cascade classifier is used to extract features of DNA image, and achieve segmentation feature recognition. Simulation results show that the improved method has the efficient ability to evaluate the DNA image with a high rate of infection feature recognition.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Zhongyi Hu
PY  - 2015/04
DA  - 2015/04
TI  - Analysis of DNA molecular genetics features in infected styphnolobium japonicum
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.222
DO  - https://doi.org/10.2991/amcce-15.2015.222
ID  - Hu2015/04
ER  -