Handwriting digital recognition method and device

Abstract

The invention discloses a handwriting digital recognition method and a handwriting digital recognition device. The method comprises the following steps of acquiring a target figure and an image data set in a target image which are to be recognized, wherein the image data set comprises at least one piece of image data; performing vector conversion on each piece of image data in the image data set to obtain vector data corresponding to each piece of image data, wherein the vector data forms a vector data set; performing dimension reduction on the vector data set by using a local sparse linear embedding dimension reduction method based on an orthogonal matching tracing algorithm to obtain a dimension reduction vector data set; and according to the dimension reduction vector data set, identifying a digital image corresponding to the target figure in the target image. Not all of computational solutions obtained by the orthogonal matching tracing algorithm in the method are zero. Compared with the prior art, the method and the device have the advantages that local sparsity can be obviously embodied, stability is realized, and the accuracy of the digital image which is finally recognized is relatively high.

Description

technical field [0001] The present application relates to the field of computer application technology, in particular to a method and device for recognizing handwritten digits. Background technique [0002] Handwritten digit recognition technology has received more and more attention in real life. Handwritten digit recognition technology refers to: after acquiring the image data in the target image, identify the same number in the target image as the target number according to the acquired image data. Since the acquired image data are all high-dimensional spatial data, before the target number recognition, the dimensionality reduction processing of its space is performed first. For example, in existing handwritten digit recognition schemes, a local sparse linear embedding dimensionality reduction method based on the least squares algorithm is usually used to reduce the dimensionality of the vector data corresponding to the high-dimensional image data, and then the K-nearest ...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved in this application is to provide a handwritten digit recognition method and device to solve the problem that the existing digit recognition scheme cannot achieve an effective sparse effect and does not have instability, which makes the accuracy of digit recognition low. question

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