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基于支持向量机方法的多目标图像分割 被引量：4

Segmentation of Multi-Target Image Based on SVM
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摘要 在核主成份分析的特征提取基础上,采用支持向量机方法对多目标图像进行分割研究.实验结果表明,结合核主成份分析的特征提取,支持向量机方法是一种很有前景的多目标图像分割技术. This paper investigates the segmentation of multi-target image based on SVM approach combining feature extraction of kernel PCA. Experimental results show that SVM approach is a promising technique for segmentation of multitarget image combining feature extraction of kernel PCA.
作者 徐海祥 曹万华 陈炜 郭丽艳
机构地区 哈尔滨工程大学计算机科学与技术学院 武汉数字工程研究所 武汉理工大学交通学院
出处 《微电子学与计算机》 CSCD 北大核心 2009年第4期5-10,共6页 Microelectronics & Computer
关键词 多目标图像分割 支持向量机 核主成份分析 segmentation of multi-target image support vector machine （SVM） kernel principal component analysis
分类号 TP31 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献26

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二级参考文献23

  • 1徐海祥,朱光喜,张翔,田金文,彭复员.基于改进的一对一支持向量机方法的多目标图像分割[J].微电子学与计算机,2005,22(12):51-54. 被引量：4
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共引文献33

同被引文献42

  • 1杜峰,施文康,邓勇,朱振幅.红外序列图像的支持向量机分割方法[J].光电工程,2005,32(3):62-65. 被引量：9
  • 2赵衍运,蔡安妮.使用支持向量机分割指纹图像的方法[J].北京邮电大学学报,2006,29(2):38-41. 被引量：6
  • 3郭兴旺,高功臣,吕珍霞.主分量分析法在红外数字图像序列处理中的应用[J].红外技术,2006,28(6):311-314. 被引量：6
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  • 9Mizushima A, Lu Renfu. An image segmentation method for apple sorting and grading using support vector machine and Otsu's method [-J]. Computers and Electronics in Agriculture, 2013, 94: 29-37.
  • 10Lazaros Nalpantidis,Georgios Ch. Sirakoulis Antonios Gasteratos. A dense stereo correspondence algorithm for hardware implementation with enhanced disparity selection[C]//SETN 2008. Greece, 2008 :365-370.

引证文献4

二级引证文献11

微电子学与计算机
2009年 第4期

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