抗混叠轮廓波变换的脱线中文手写体笔迹识别

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％.%In order to enhance the precision rate of off-line Chinese handwriting-based writer identification,a new feature extraction 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" phenomenon in the reconstructed image.In comparison with a single wavelet transform,the complex wavelet transform and Contourlet transform,the method increases the accuracy about 22.5%,7.7%,2.5%,respectively.