Paper
31 December 2010 Image-based automatic recognition of larvae
Ru Sang, Guiying Yu, Weijun Fan, Tiantai Guo
Author Affiliations +
Proceedings Volume 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation; 75443E (2010) https://doi.org/10.1117/12.885399
Event: Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 2010, Hangzhou, China
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.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ru Sang, Guiying Yu, Weijun Fan, and Tiantai Guo "Image-based automatic recognition of larvae", Proc. SPIE 7544, Sixth International Symposium on Precision Engineering Measurements and Instrumentation, 75443E (31 December 2010); https://doi.org/10.1117/12.885399
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Cited by 2 scholarly publications.
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KEYWORDS
Feature extraction

Image segmentation

Image processing

Image compression

Pattern recognition

Detection and tracking algorithms

Databases

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