(untitled) (International Journal of Engineering and Computer Science, 2014)
In This paper, the face images retrieved system based on Lifting wavelet transforms with principal component analysis (PCA). These techniques are implemented and their performances are investigated using frontal facial images from the ORL database. The retrieval accuracy compare with different distance methods like Euclidean distance and Manhattan distance. Lifting wavelet Transform(LWT) is effective representing in image features and is suitable in Face image retrieval, it still encounters problems especially in implementation. e.g. Floating point operation and decomposition speed. We use the advantages of lifting scheme, a spatial approach for constructing wavelet filters, which provides feasible alternative for problems facing its classical counterpart. Lifting scheme has such intriguing properties as convenient construction, simple structure, integer-to-integer transform, low computational complexity as well as flexible adaptivity, revealing its potentials in Face image retrieval. Lifting wavelet transform with PCA gives less computation and high retrieval rate.