Abstract: As shape feature descriptors, high dimention zernike moments have the function of describing the detail information of image region, which exist "dimension disaster". This will result to increase the complexity of the algorithm and unnecessary information which make major information confused, and will affect decribing the content of the image.A new algorithm based on Manifold method was proposed to realize dimension deduction in image data. Under the condition of Laplace figure keeping local sample data, overall algorithm was introduced to ensure the integrity of the sample. Considering the influence of the correlation between information on projection accuracy,schur cigenvaluc decomposition was made to obtain the orthogonal vectors. This can make the data reconstruction relatively easier, and the rotation invariant of Zernike moment can still keep down, then making the image retrieval accords with the human visual effect. This method is superior than LPP in the retrieval performance, and retrieval results arc significantly improved.

Key words: Zernike moment, Image retrieval, PCA, LPP, Schur decomposition