Title :
A Research on the Recognition of Chironomid Larvae Based on SVM
Author :
Zhao, Jing-Ying ; Guo, Hai ; Sun, Xing-Bin
Author_Institution :
Dept. of Comput. Sci.& Eng., Dalian Nat. Univ., Dalian, China
Abstract :
The traditional method of detecting Chironomid larvaes and plankton mostly is manual identification, which is inefficient. This paper puts forward the Chironomid larvae recognition method which is based on the support vector machines. The Chironomid larvae images are decomposed using a wavelet from which the features were extracted and kernel function is used. The experiment shows that the recognition rate is up to 86%, which demonstrates the effectiveness of this method.
Keywords :
environmental science computing; image recognition; support vector machines; water quality; wavelet transforms; Chironomid larvae recognition; SVM; support vector machines; Circuits; Image analysis; Image recognition; Kernel; Marine vegetation; Monitoring; Pattern recognition; Support vector machine classification; Support vector machines; Water resources; Chironomid larvae recognition; biometric recognition; support vector machines;
Conference_Titel :
Circuits, Communications and Systems, 2009. PACCS '09. Pacific-Asia Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3614-9
DOI :
10.1109/PACCS.2009.70
