NEURAL NETWORK BASED HANDWRITING ANALYSIS SYSTEM

Abstract

ABSTRACT A neural network based handwriting analysis system (100) comprising data processing module (102) configured to collect and prepare handwriting data, including standardizing handwriting sample images, a convolutional neural network (CNN) layer (104) configured to extract visual features from handwriting, including line slants, spacing, and pressure variations, a deep neural network (DNN) classifier layer (106) configured to classify handwriting data based on extracted features to predict personality traits; and an evaluation module (108) to interpret model predictions and evaluate performance metrics on unseen handwriting samples. <>

Specification

Description:FIELD OF THE DISCLOSURE
[0001] This invention generally relates to the field of neural network-based handwriting analysis systems, specifically systems for the sentimental analysis of handwriting samples to predict the writer's personality traits.
BACKGROUND

[0002] The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also correspond to implementations of the claimed technology.
[0003] Analysis of handwriting to understand personality traits, known as graphology, is traditionally manual and subjective. With the advent of artificial intelligence (AI), neural networks can now automate the analysis, prov , Claims:1. A neural network based handwriting analysis system (100), comprising:
data processing module (102) configured to collect and prepare handwriting data, including standardizing handwriting sample images;
a convolutional neural network (CNN) layer (104) configured to extract visual features from handwriting, including line slants, spacing, and pressure variations;
a deep neural network (DNN) classifier layer (106) configured to classify handwriting data based on extracted features to predict personality traits; and
an evaluation module (108) to interpret model predictions and evaluate performance metrics on unseen handwriting samples.

2. The neural network based handwriting analysis system (100) as claimed in claim 1, wherein the system (100) operates on a cloud-based platform to enable scalability and remote access.

3. The neural network based handwriting analysis system (100) as claimed in claim 1, wherein the CNN layer (104) is designed to output feature maps to be fed into the DNN classifier layer (106

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