计算机科学 ›› 2014, Vol. 41 ›› Issue (1): 311-.
• 图形图像与模式识别 • 上一篇
韩姗姗,黄凯,王万良,郑建炜,蒋一波
HAN Shan-shan,HUANG Kai,WANG Wan-liang,ZHENG Jian-wei and JIANG Yi-bo
摘要: 在传统DCV的基础上,提出了一种改进的快速DCV分类方法。该方法与传统的DCV分类方法相比,在保证识别率相同的情况下具有较快的分类速率。传统的DCV分类方法通过计算特征向量之间的距离来进行分类,而所提快速DCV分类方法则通过标量计算完成分类。理论分析及复杂度计算表明,快速DCV分类方法的分类速率是传统DCV分类方法的2倍左右,在Yale、ORL和PIE 3种人脸数据库得到的对比仿真实验结果验证了该算法的有效性。
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