Feature generation using the Laplacian operator with Neumann boundary condition

被引:1
|
作者
Khabou, Mohamed A. [1 ]
Rhouma, Mohamed B. H. [2 ]
Hermi, Lotfi [3 ]
机构
[1] Univ West Florida, Dept Elect & Comp Engn, Pensacola, FL 32514 USA
[2] Sultan Qaboos Univ, Dept Math & Stat, Muscat, Oman
[3] Univ Arizona, Dept Math, Tucson, AZ 85721 USA
关键词
D O I
10.1109/SECON.2007.343005
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The eigenvalues of the Neumann Laplacian are used to generate three different sets of features for shape recognition and classification in binary images. The generated features are rotation, translation, and size invariant and are shown to be tolerant of boundary deformation. The effectiveness of these features is demonstrated by using them to classify 5 types of computer generated and hand drawn shapes. The classification was done using 4 to 20 features fed to a simple feedforward neural network. Correct classification rates ranging from 94.4% to 100% were obtained on computer generated shapes and 67.5% to 95.5% on hand drawn shapes.
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页码:766 / +
页数:2
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