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| 基于小波分析的红虫识别 | |
| 引用本文： | 赵晶莹,孙兴滨,吕伟民,崔福义.基于小波分析的红虫识别[J].东北林业大学学报,2009,37(4). |
| 作者姓名： | 赵晶莹 孙兴滨 吕伟民 崔福义 |
| 作者单位： | 1. 大连民族学院,大连,116600 2. 东北林业大学 3. 黑龙江省轻工科学研究院 4. 哈尔滨工业大学 |
| 基金项目： | 国家自然科学基金，黑龙江省自然科学基金，中国博士后科学基金，黑龙江省博士后启动基金，国家民委项目 |
| 摘 要： | 提出了一种能量特征与支持向量机(Support Vector Machine,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. |
| 关 键 词： | 红虫识别 小波分解 支持向量机 核函数 |
Recognition of Chironomid Larvae Based on Wavelet Analysis |
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| Zhao Jingying,Sun Xingbin,Lü Weimin,Cui Fuyi.Recognition of Chironomid Larvae Based on Wavelet Analysis[J].Journal of Northeast Forestry University,2009,37(4). | |
| Authors: | Zhao Jingying Sun Xingbin Lü Weimin Cui Fuyi |
| Abstract: | 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. |
| Keywords: | Chironomid larvae recognition Wavelet decomposition Support vector machines Kernel functions |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |