中文摘要：

提出了一种能量特征与支持向量机（SupportVectorMachine，SVM）相结合的红虫与水中浮游生物图像识别方法。把小波能量特征加入到原始图像中，再用Fisher线性判别法进行特征提取，同时提取图像的三层小波分解后系数的数学特征和图像颜色调和熵构造特征向量，然后采用SVM进行识别。通过对红虫及浮游生物的分类进行实验，验证了该方法的有效性，获得较高的识别率。

英文摘要：

An image recognition method for chironomid larvae and plankton is developed based on wavelet energy feature and Support Vector Machines（SVM）. The wavelet energy feature is added to the original images, Fisher＇s linear discriminant method is applied to feature extraction, and then wavelet decomposition and color information entropy are selected to construct vectors for SVM that is used to classify the images. The experiment proves that the method is efficient and has a high recognition rate.