Palm print identification method based on projection operator and wavelet transform

Abstract

The invention belongs to a palm print identification method based on subspace characteristic extraction and especially relates to a palm print identification method based on a projection operator and a wavelet transform. The method comprises the following steps of constructing a palm print database; carrying out the wavelet transform on an image in the palm print database; using palm print data after the wavelet transform to construct a null space of the projection operator; using a singular value decomposition method to calculate a discriminating projection of the space; using the discriminating projection to carry out characteristic extraction on the palm print data so as to obtain the palm print database after dimension reduction; after the wavelet transform is performed on a palm print image to be tested, using the discriminating projection to carry out dimension reduction, and then using the palm print database after the dimension reduction and using a nearest neighbor classifier to classify a sample to be tested after the dimension reduction. The method has advantages that certain robustness is possessed; the method is insensitive to changes of palm print image illumination; the projection operator is used and a space decomposition property is possessed; a dimension of a decomposed subspace is fixed so that a condition that a characteristic dimension is selected by a person in other methods is avoided.

Description

technical field [0001] The invention belongs to a palmprint recognition method based on subspace feature extraction, in particular to a palmprint recognition method based on projection operator and wavelet transform. Background technique [0002] At present, people's work and life are more and more inseparable from identification and identity verification. As a new identification technology, palmprint recognition technology has received more and more attention. How to represent palmprints is a difficult point and a hotspot in palmprint recognition. Effective representation of palmprint is the key to improve the performance of palmprint recognition technology, and the feature extraction method based on subspace is one of the effective methods to represent palmprint. It is supported by statistical theory and has achieved good results. However, in the feature extraction method based on subspace, the dimension of the feature generally needs to be set artificially, which affects...

AI Technical Summary

Problems solved by technology

However, in the feature extraction method based on subspace, the dimension of the feature generally needs to be set artificially, which affects the practicability of the method

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