Handwritten Digit Recognition Method Based on Sparse Transformation

A digital recognition and sparse transformation technology, applied in the field of pattern recognition, can solve problems such as data information redundancy, and achieve the effects of simple calculation, good recognition rate, and improved operating efficiency
CN104850870BInactive Publication Date: 2018-07-03XIAN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Patents(China)
Current Assignee / Owner
XIAN UNIV OF TECH
Publication Date
2018-07-03
Estimated Expiration
Not applicable Β· inactive patent

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Abstract

The invention discloses a sparse transform-based handwritten digit recognition method. The method includes the following steps of: pre-processing read training data; training the pre-processed training data with an objective function so as to obtain a transform matrix W; performing sparse transform on data to be detected to obtain a sparse representation coefficient x'; and based on a nearest neighbor rule, comparing the sparse representation coefficient x' of the data to be detected with various classifications of class tags, and finding a class tag most similar to a sample to be detected, and classifying the sample to be detected to a classification to which the class tag belongs, and finishing recognition of handwritten digits. With the sparse transform-based handwritten digit recognition method of the invention adopted, after being subjected to the sparse transform, the data to be detected has sparsity, and therefore, computation is simple, and operation efficiency can be improved.
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Description

technical field

[0001] The invention belongs to the technical field of pattern recognition, and in particular relates to a method for recognizing handwritten digits based on sparse transformation. Background technique

[0002] With the promotion of information network, there is a large amount of data to be input into computer network. Moreover, in the modern information society, all aspects must deal with numbers. As an important branch of pattern recognition, handwritten digit recognition has a wide range of applications in postal, taxation, transportation, financial and other industries. Not only that, handwritten digit recognition is used in some large-scale data statistics, such as industry annual inspection, population It can also be applied to fields such as censuses that require a lot of manpower and material resources.

[0003] For identification or classification, data representation needs to highlight salient features, but in practice, the digital sampling proces...

Claims

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