Handwritten digit recognition method and device on basis of image covariance characteristics

Abstract

The invention discloses a handwritten digit recognition method and device on the basis of image covariance characteristics. The method includes: extracting covariance matrixes of N handwritten digit training images, and using the covariance matrixes as training samples, wherein N is a natural number; utilizing a support vector machine to train the training samples to obtain classifier model coefficients, wherein the kernel function adopted by the support vector machine is a matrix kernel function for calculating similarity among the covariance matrixes; utilizing the classifier model coefficients, the matrix kernel function and the training samples to build a classifier model; utilizing the classifier model to recognize handwritten digit images which need to be recognized. The support vector machine adopting the matrix kernel function can be used for processing the image covariance characteristics, therefore the generated classifier model coefficients are more accurate, and recognition rate of handwritten digits is improved further.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a handwritten numeral recognition method and device based on image covariance features. Background technique [0002] In recent years, with the rapid development of computer technology and digital image processing technology, handwritten digit recognition technology has been widely used in industries such as large-scale data statistics, mail sorting, property and taxation. At the same time, support vector machines have been widely used in the field of handwritten digit recognition due to their unique advantages. [0003] Researchers have found that using the image covariance matrix as an image recognition feature will improve the image recognition rate. However, in the prior art, the support vector machine can only process the vector features of the image to recognize the image, and cannot recognize the image according to the covariance feature of the image. Therefore,...

AI Technical Summary

Problems solved by technology

However, in the prior art, the support vector machine can only process the vector features of the image to recognize the image, and cannot recognize the image according to the covariance feature of the image. Therefore, there is an urgent need for a handwritten digit recognition method based on the image covariance feature and device to improve the recognition rate of handwritten digits

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