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Proceedings Paper

Image-based automatic recognition of larvae
Author(s): Ru Sang; Guiying Yu; Weijun Fan; Tiantai Guo
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Paper Abstract

As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

Paper Details

Date Published: 31 December 2010
PDF: 6 pages
Proc. SPIE 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 75443E (31 December 2010); doi: 10.1117/12.885399
Show Author Affiliations
Ru Sang, China Jiliang Univ. (China)
Guiying Yu, China Jiliang Univ. (China)
Weijun Fan, China Jiliang Univ. (China)
Tiantai Guo, China Jiliang Univ. (China)

Published in SPIE Proceedings Vol. 7544:
Sixth International Symposium on Precision Engineering Measurements and Instrumentation
Jiubin Tan; Xianfang Wen, Editor(s)

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