【摘要】 线性鉴别分析(LDA)是模式识别领域广泛使用的一种特征抽取方法,而在图像识别中,由于小样本问题,经常采用的是PCA+LDA方法来代替单纯的LDA。提出了一种多频带线性鉴别分析方法(MBLDA),使LDA在完整的样本空间上进行,而且解决了小样本问题。MBLDA不仅避免了PCA过程带来的信息损失,而且提取的鉴别特征维数小,还提高了识别性能。该方法在识别精度上大幅度地超越了PCA和LDA或PCA+LDA,通过对ORL,NUST603人脸库的实验验证了该算法的有效性。更多还原

【Abstract】 Linear Discriminant Analysis(LDA) is the well-known method in pattern recognition,and researchers usually use PCA+LDA instead of LDA due to the Small Sample Size Problem(SSSP) in image recognition.A Multi-band Linear Discriminant Analysis(MBLDA) is proposed,by which LDA is established on the whole samples space and SSSP is resolved.Based on MBLDA,the data loss using PCA is avoided,the dimension of discrimination feature extracted is very low and the recognition performance is advanced.Its recognition rate exceeds PCA,LDA,or PCA+LDA largely.Some experiments on ORL and NUST603 face database demonstrate that the proposed method is effective.更多还原