Study of Key Algorithm on Automatic Classification of Insect Images

DOI

10.2991/iccsae-15.2016.70How to use a DOI?

Keywords

Image Similarity, Image Feature analysis, Color Histogram, Textural Features, Insect Species Identification

Abstract

Insects, due to their diversity, are the largest group of creature on earth, many of which are yet to be discovered right now. As the photographic hardware develops and gets pervasive rapidly, insect images or pictures have become an important approach for insect researchers to conduct scientific study. However, considering the huge volume of insect image data, researchers usually are not interested in all the images and instead, hope to categorize these images preliminarily and then hand them on for manual processing, which will significantly improve work efficiency and reduce manual workload. In this paper, color histogram and textural features are adopted to collect image features which then use clustering analysis method for automatic classification of insect species. The experimental result is quite good. And on the basis of this, more image features can be extracted to gain more accurate results, or program efficiency can be optimized through parallelization, during which a species feature database is gradually established to have automatic comparison and identification of insect features.

Copyright

© 2016, 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  - Jian Li
AU  - Lei Zhang
AU  - BaoPing Yan
PY  - 2016/02
DA  - 2016/02
TI  - Study of Key Algorithm on Automatic Classification of Insect Images
BT  - Proceedings of the 2015 5th International Conference on Computer Sciences and Automation Engineering
PB  - Atlantis Press
SP  - 364
EP  - 369
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccsae-15.2016.70
DO  - 10.2991/iccsae-15.2016.70
ID  - Li2016/02
ER  -