基于Haar小波变换和分块DCT的人脸识别

Face recognition based on Haar wavelet transform and block DCT

提出一种新的基于二维离散小波分解和分块离散余弦变换的降维方法。该方法与模式识别领域中用于特征提取和降维的PCA-LDA方法进行了比较。结果表明,此方法与PCA-LDA方法在识别率上大体相当,但它比其更具有计算量小、降维速度快的优点。因此,该方法对于人脸识别是一种有效降维手段。

A new dimension reduction method was proposed based on two dimension discrete wavelet decomposition and block discrete cosine transform. The new method was compared with the famous PCA-LDA method which was widely used for feature extraction and dimension reduction in pattern recognition. The experimental results show that the new method could get approximately equal retrieval accuracy to PCA-LDA method, but it performed better in calculation complexity and speed than the latter. So the proposed method is an effective dimension reduction means for face recognition.