What Is The Use Of Machine Learning Handwriting Recognition
  • Download Apps
25k+
close Image

What is the Use of Machine Learning Handwriting Recognition

A
by Alan Jackson — 2 years ago in Machine Learning 2 min. read
2255

We examine how machine learning techniques can be used to solve handwriting recognition issues

Recent Deep Learning advancements, such as the introduction of transformer topologies, have helped us accelerate our handwritten character recognition. Intelligent Character Recognition (ICR), is a term used to describe the process for recognizing handwritten content. ICR algorithms require more intelligence than ordinary OCR.

This post will cover the challenges of handwritten text identification and the techniques that can be used to tackle them using deep learning and machine learning.

Machine Learning to Handwrite Recognition Applications

Healthcare and Pharmaceuticals

In the healthcare/pharmaceutical industry, patient medication digitization is a serious issue. Roche processes millions of PDFs each day, processing petabytes in medical PDFs. Handwritten character recognition is also important in areas such as patient enrollment and form digitization. Handwriting analysis can be a great service for hospitals and pharmaceutical companies.

Insurance

An insurance company that is large receives more than 20 million documents each day. A delay in processing a claim can have a serious impact on the business. There may be a variety in the claims documents, so relying on only human processing can slow down the process.

Also read: 5 Best Resource Capacity Planning Tools for Teams

Banking

Regularly, people write checks. They continue to play an important role in most non-cash transactions. In many developing countries, the current check processing method involves staff at a bank to manually enter the information on cheques and verify data like signature and date. A handwriting textual recognition system is a cost-saving tool that can be used to save time and money on bank processing.

Online Libraries

Images of historic knowledge are being digitalized and made accessible to the public by uploading scans. This effort will not be effective if the text within the photos cannot be identified and indexed, queried, and browsed. Handwriting identification is crucial for bringing twentieth-century papers, postcards and research works alive.



Techniques

In the initial attempts to recognize handwriting, ML methods like Hidden Markov Models (HMM), SVM, and others were used. After pre-processing the text, feature extraction is used for identifying key information about each character. This includes loops, tipping points, aspect ratios, and so forth. These features are then passed to a classifier like HMM to get the results. The machine-learning algorithms‘ performance can be limited by the manual feature extraction and their low learning capacity. It is not scaleable because the feature extraction stage for each language is different. The handwriting recognition rate has increased dramatically since the introduction of deep learning.

Challenges in Handwriting Recognition

  1. There are many variations in strokes, and each person will have their own interpretation.
  2. The handwriting style of a user can also vary from time to time, and it may be uneven.
  3. Poor quality has been caused by the gradual degradation of the source text.
  4. On white paper, people don’t need to write text in one direction. However, text printed on paper is straight.
  5. With cursive handwriting, it is difficult to recognize characters and distinguish them from one another.
  6. Handwritten text may exhibit a different rotation than printed text.
  7. It is more expensive to acquire a dataset that can be used to learn than synthetic data.
A
Alan Jackson

Alan is content editor manager of The Next Tech. He loves to share his technology knowledge with write blog and article. Besides this, He is fond of reading books, writing short stories, EDM music and football lover.

Top 10 News

view all
Follow us on

Categories

Related Posts

img

Machine Learning

What Is Deep Learning? How It Works, Techniques & Appli...
By: Micah James, Sun February 4, 2024

Deep learning stands out as an innovative technology in artificial intelligence..

img

Machine Learning

The Role Of Machine Learning in DSaaS
By: Micah James, Mon December 18, 2023

Numerous cloud-based services allow organizations to access the tools and..

img

Machine Learning

Machine Learning For Object Detection In Self Driving Cars
By: Micah James, Tue December 5, 2023

Verdict: Self-driving cars are paramount with machine learning for object..

img

Machine Learning

5 Advantages Of Using Machine Learning In Game Development
By: Alan Jackson, Thu November 30, 2023

Machine Learning (ML) is contributing its entirety to design and develop games..

img

Machine Learning

Everything You Need To Know About Liquid Neural Networks
By: Evelyn Addison, Mon September 11, 2023

With the passage of time, artificial intelligence and machine learning continue..

img

Machine Learning

Big Data in ESG: A New Frontier in Sustainable Business Prac...
By: Alan Jackson, Fri September 1, 2023

In the modern business landscape, the significance of Environmental, Social,..

Subscribe
Notify of
guest
0 Comments
Inline Feedbacks
View all comments

Copyright © 2018 – The Next Tech. All Rights Reserved.