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An application of linear SVM to fingerprint image segmentation

机译:线性SVM在指纹图像分割中的应用

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An exact fingerprint image segmentation improves the accuracy of automatic fingerprint identification system and reduces the processing time of follow-up process. A novel fingerprint image segmentation method based on linear Support Vector Machine (SVM) is proposed to overcome the shortcomings of present approaches shown in previous literatures. Feature vectors are constructed by Fourier spectrum energy ratio and gray contrast extracted from sub-blocks of the fingerprint image. Then these feature vectors are classified by linear SVM, morphological operations are performed to realize fingerprint image segmentation in the end. Experimental results show that this method is precise and reliable compared with other approaches.
机译:精确的指纹图像分割提高了自动指纹识别系统的准确性,并减少了后续处理的处理时间。 提出了一种基于线性支持向量机(SVM)的指纹图像分割方法,克服了先前文献中所示的当前方法的缺点。 特征向量由从指纹图像的子块提取的傅里叶频谱能量比和灰色对比度构成。 然后,这些特征向量由线性SVM分类,执行形态操作以实现终点的指纹图像分割。 实验结果表明,与其他方法相比,该方法精确可靠。

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