| 基于支持向量机的局域线性嵌入算法在图像检索中的应用 |
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| 引用本文： | 张银霞,邓文新.基于支持向量机的局域线性嵌入算法在图像检索中的应用[J].齐齐哈尔大学学报(自然科学版),2009,25(4):14-17. |
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| 作者姓名： | 张银霞 邓文新 |
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| 作者单位： | 齐齐哈尔大学,黑龙江齐齐哈尔,161006 |
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| 摘 要： | SVM算法复杂度与样本维数无关,具有的泛化能力强、分类精度高的特点,而LLE是有效的非线性降维方法,本文利用支持向量机(SVM)算法对局域线性嵌入(LLE)算法进行改进,有效地解决了基于内容的图像检索中的高维特征向量的降维问题,实验表明具有较高的查全率和查准率.
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| 关 键 词： | 支持向量机 局域线性嵌入 图像检索 |
Application of locally linear embedding algorithm based on support vector machine in image retrieval |
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| ZHANG Yin-xia,DENG Wen-xin.Application of locally linear embedding algorithm based on support vector machine in image retrieval[J].Journal of Qiqihar University(Natural Science Edition),2009,25(4):14-17. |
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| Authors: | ZHANG Yin-xia DENG Wen-xin |
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| Institution: | Qiqihar University;Heilongjiang Qiqihar 161006;China |
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| Abstract: | SVM has the generalization ability and high precision classification,and the algorithm complexity has nothing to do with the dimension of samples,LLE is an effective non-linear dimension reduction methods.This paper improved Locally Linear Embedding(LLE) algorithm used with Support Vector Machine(SVM) algorithm,and solved the dimension reduction problems of high-dimensional characteristics vector in the content-based image retrieval.The experiments showed that has high accurate rate and complete rate. |
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| Keywords: | support vector machine locally linear embedding image retrieval |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
