ZENG Xiang-jin, HUANG Xin-han, WANG Min. Application of Invariant Moment’s Improved Support Vector Machine to Micro-target Identification[J]. ROBOT, 2009, 31(2): 118-123.
Citation: ZENG Xiang-jin, HUANG Xin-han, WANG Min. Application of Invariant Moment’s Improved Support Vector Machine to Micro-target Identification[J]. ROBOT, 2009, 31(2): 118-123.

Application of Invariant Moment’s Improved Support Vector Machine to Micro-target Identification

  • In order to identify multi micro parts,an improved SVM(support vector machine) algorithm is presented, which employs invariant moments based on edge extraction to obtain feature attribute and then presents a heuristic attribute reduction algorithm based on rough set's discernable matrix to obtain attribute reduction.At last,SVM is used to identify and classify the targets.The effect on identifying multi micro parts by SVM is compared with that by the proposed improved SVM.The experiment results under micro vision environment show that the proposed improved SVM classification method can meet the system application requirements,with the resolution of 95 percents.
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