Research on the recognition of chironomid larvae based on SVM

Jingying Zhao; Hai Guo; Xing-bin Sun

doi:10.1117/12.836704

10 July 2009 Research on the recognition of chironomid larvae based on SVM

Jingying Zhao, Hai Guo, Xing-bin Sun

Proceedings Volume 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering; 74891D (2009) https://doi.org/10.1117/12.836704
Event: International Conference on Photonics and Image in Agriculture Engineering (PIAGENG 2009), 2009, Zhangjiajie, China

Abstract

The traditional method of detecting Chironomid larvaes and plankton in water mostly is observation by Naked Eye, which is inefficient and inaccurate. This paper puts forward the Chironomid larvae image recognition method which is based on the support vector machines and multi-layered wavelet decomposition. Gradation histogram balance strengthening treatment is carried out for the image, so as to improve the contrast ratio and make for the threshold division. For each image, a 36 dimension feature vector is computed via two-level discrete Wavelet transform (DWT). The last step of the proposed approach consists is using support vector machine(SVM) as classifer and Wavelet energy as features to recognize the images. Extensive classification experiments on our image data validate that it is promising to employ the proposed texture features to recognize Chironomid larvaes in image.

Citation Download Citation

Jingying Zhao, Hai Guo, and Xing-bin Sun "Research on the recognition of chironomid larvae based on SVM", Proc. SPIE 7489, PIAGENG 2009: Image Processing and Photonics for Agricultural Engineering, 74891D (10 July 2009); https://doi.org/10.1117/12.836704

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