With the aim to meet the requirements of multi-directional choice, the paper raise a new approach to the invariant feature extraction of handwritten Chinese characters, with ridgelet transform as its foundation. First of all, the original images will be rotated to the Radon circular shift by means of Radon transform. On the basis of the characteristic that Fourier transform is row shift invariant, then, the one-dimensional Fourier transform will be adopted in the Radon domain to gain the conclusion that magnitude matrixes bear the rotation-invariance as a typical feature, which is pretty beneficial to the invariant feature extraction of rotation. When such is done, one-dimensional wavelet transform will be carried out in the direction of rows, thus achieving perfect choice of frequency, which makes it possible to extract the features of sub-line in the appropriate frequencies. Finally, the average values, standard deviations and the energy values will form the feature vector which is extracted from the ridgelet sub-bands. The approaches mentioned in the paper could satisfy the requirements from the form automatic processing on the recognition of handwritten Chinese characters.
This paper studied a new method of ROI extraction based on quaternion matrix. Firstly, the image is cut into sub-blocks, and the Candidate region is gained by image entropy. Then the greatest expression of sub-blocks is obtained by svd of quaternion matrixs, and the relationship between the image blocks is found according to the definition of quaternion inner product. At last, dimensionality reduction of incidence matrix is carried out with Isomap, and in this process the ROI is extracted. The results of experiments confirm the feasibility and efficiency of this method.
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