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中文摘要：
为了进一步提高脱线中文手写体笔迹识别的正确率,提出了一种基于抗混叠轮廓波变换的特征提取算法。抗混叠轮廓波变换不仅具有轮廓波变换的多尺度、多方向特性,同时克服了轮廓波变换中频谱混叠的现象,避免了重构图像出现＂划痕＂现象。实验结果证明,抗混叠轮廓波变换的GGD模型与使用单小波、复小波、轮廓波变换的GGD模型方法比较,识别正确率分别提高了23.5%、7.7%、2.5%。
英文摘要：
In order to enhance the precision rate of off-line Chinese handwriting-based writer identification,a new feature ex-traction method based on the non-aliasing Contourlet transform is presented.The transform not only has the multiscale and multidirection properties,moreover it overcomes the frequency aliasing of Contourlet transform,and avoids＂scratching＂phe-nomenon in the reconstructed image.In comparison with a single wavelet transform,the complex wavelet transform and Con-tourlet transform,the method increases the accuracy about 22.5%,7.7%,2.5%,respectively.
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