Freehand graph classification method and system based on error back propagation algorithm

Abstract

The invention discloses a hand-drawn graph classification method and system based on an error back propagation algorithm, relates to the technical field of neural networks, and is used for solving the problem that hand-drawn graph data cannot be effectively classified in the prior art. According to the technical key points, the method comprises the following steps: designing one or more regular graph description templates; acquiring hand-drawn image data according to the regular graph drawing template; preprocessing the hand-drawn image data; constructing and training a BP neural network model; and inputting to-be-classified hand-drawn image data into the trained BP neural network model to obtain a classification result. According to the method, fine differences between writing tracks can be distinguished, and whether a writer has tremor or not can be more accurately divided. The method can be applied to clinical medical treatment to judge whether the hands of the patient have tremor or not.

Description

technical field [0001] The invention relates to the technical field of neural networks, in particular to a hand-painted graphic classification method and system based on an error backpropagation algorithm. Background technique [0002] As an activity controlled by the human advanced nervous system, handwriting depends on the participation of multiple parts of the brain, as well as the coordination of the muscles and skeletal systems. From the perspective of muscle activity, the handwriting process is jointly completed by multiple muscle groups through continuous and overlapping coordinated activities. Tremor in one side of the limb or hand can sometimes affect writing. For example, tremor writing exists in patients with Parkinson's disease and patients with cerebral hepatolenticular degeneration. Hand tremors can be seen in a variety of nervous system diseases, such as essential tremor, Parkinson's disease, hepatolenticular degeneration, dystonic tremor, cerebellar tremor a...

AI Technical Summary

Problems solved by technology

[0003] In view of the above problems, the present invention proposes a hand-drawn graphics classification method and system based on error back propagation algorithm, in order to solve the problem that the prior art cannot handle hand-painted image data Problems with Effective Classification

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