A chironomid larvae images recognition method based on wavelet energy feature and improved KNN is developed. Wavelet decomposition and color information entropy are selected to construct vectors for KNN that is used t...A chironomid larvae images recognition method based on wavelet energy feature and improved KNN is developed. Wavelet decomposition and color information entropy are selected to construct vectors for KNN that is used to classify of the images. The distance function is modified according to the weight determined by the correlation degree between feature and class, which effectively improves classification accuracy. The result shows the mean accuracy of classification rate is up to 95.41% for freshwater plankton images, such as chironomid larvae, cyclops and harpacticoida.展开更多
基金Supported by the National Natural Science Foundation of China(50778048)(60803096)the Natural Science Foundation of Hei-longjiang Province(E200812)China Postdoctoral ScienceFoundation Funded Project(20070420882)~~
文摘A chironomid larvae images recognition method based on wavelet energy feature and improved KNN is developed. Wavelet decomposition and color information entropy are selected to construct vectors for KNN that is used to classify of the images. The distance function is modified according to the weight determined by the correlation degree between feature and class, which effectively improves classification accuracy. The result shows the mean accuracy of classification rate is up to 95.41% for freshwater plankton images, such as chironomid larvae, cyclops and harpacticoida.
