Master Thesis of OCR using deep learning - Pavel Andrlik, 2022

Thanks for another citation by Pavel Andrlik, at the Master Thesis on OCR using deep learning.

University of West Bohemia
Faculty of Applied Sciences
Department of Cybernetics
(Czech Republic)

The author has been highlight my paper over the classification method choice on using Support Vector machine...[]

 Abstract of the Thesis

This diploma thesis deals with the problem of optical character recognition (OCR) using neural networks. I am focusing on improving text detection and OCR by fine-tuning an E2E-MLT scene text detector by training it on synthetic data which emulates real data. The model was fine-tuned on several datasets with synthetically generated data and real data, then the models were tested on one synthetic and two real datasets, one with the majority of the wild text, the second with the majority of TV news imprinted text. On the dataset with majority of TV news imprinted texts the fine-tuned models achieved improvement by decreasing character error rate from 52% to 31.6% word error rate and from 56.5% to 22%. It was also experimentally discovered that training models on synthetic data simulating real TV news images deteriorate detection and reading model capability on wild text data.

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What I am interesting is at the motivation side!

Full Thesis Can find at: https://otik.uk.zcu.cz/bitstream/11025/48953/1/Thesis___Pavel_Andrlik.pdf

My quick reflection on the motivation side!

The use case could also apply on some written paper for data collection such as on artist idea, random articles etc. we have a lot of handwriting or piece of writing printed that should also consider as collection on our language.

A compact deep learning model for Khmer handwritten text recognition

Bayram Annanurov, Norliza Mohd Noor 

Department of Computer Science, Paragon International University, Cambodia 

Department of Engineering, Razak Faculty of Technology and Informatics, Universiti Teknologi Malaysia, Malaysia

Abstract (of the Paper)

The motivation of this study is to develop a compact offline recognition model for Khmer handwritten text that would be successfully applied under limited access to high-performance computational hardware. Such a task aims to ease the ad-hoc digitization of vast handwritten archives in many spheres. Data collected for previous experiments were used in this work. The oneagainst-all classification was completed with state-of-the-art techniques. A compact deep learning model (2+1CNN), with two convolutional layers and one fully connected layer, was proposed. The recognition rate came out to be within 93-98%. The compact model is performed on par with the state-of-theart models. It was discovered that computational capacity requirements usually associated with deep learning can be alleviated, therefore allowing applications under limited computational power.

Link To the Page 

Optical character recognition system for Baybayin scripts using support vector machine

A new publishing related to SVM method on OCR case, "Optical character recognition system for Baybayin scripts using support vector machine" -  https://peerj.com/articles/cs-360/

Thanks for citation that to have more clearer that the method could work in some other cases.

This part is delight me and remind it back.

Abstract (of the paper)

 In 2018, the Philippine Congress signed House Bill 1022 declaring the Baybayin script as the Philippines’ national writing system. In this regard, it is highly probable that the Baybayin and Latin scripts would appear in a single document. In this work, we propose a system that discriminates the characters of both scripts. The proposed system considers the normalization of an individual character to identify if it belongs to Baybayin or Latin script and further classify them as to what unit they represent. This gives us four classification problems, namely: (1) Baybayin and Latin script recognition, (2) Baybayin character classification, (3) Latin character classification, and (4) Baybayin diacritical marks classification. To the best of our knowledge, this is the first study that makes use of Support Vector Machine (SVM) for Baybayin script recognition. This work also provides a new dataset for Baybayin, its diacritics, and Latin characters. Classification problems (1) and (4) use binary SVM while (2) and (3) apply the multiclass SVM classification. On average, our numerical experiments yield satisfactory results: (1) has 98.5% accuracy, 98.5% precision, 98.49% recall, and 98.5% F1 Score; (2) has 96.51% accuracy, 95.62% precision, 95.61% recall, and 95.62% F1 Score; (3) has 95.8% accuracy, 95.85% precision, 95.8% recall, and 95.83% F1 Score; and (4) has 100% accuracy, 100% precision, 100% recall, and 100% F1 Score.

i2ocr - Free Online Khmer OCR, It works!

i2OCR.com has provided Khmer OCR free for everyone to use, I have tested and got a good enough result, I can say around 95% is OK if it is the Khmer Unicode text.

I will try out sometimes on old Limon or ABC fonts, for handwriting text is not working.

So you may try when you need: http://www.i2ocr.com/free-online-khmer-ocr

The tool now is added into my list, Khmer Tools.

Sample testing

Application of Support Vector Machine in Prediction Secondary Structure Protein

Application of Support Vector Machine in Prediction Secondary Structure Protein

NI Jabbar, RI Jabbar

This paper studying the predication of secondary structure protein from primary
structure protein using support vector machine (SVM). We classify 64 types of
proteins in three types: Helices (H), Strand (E) and Coil (C).


View Here.

Thanks for citation.

Wring Lunar Date in Khmer: Khmer Date Converter

Writing Lunar Date in Khmer is for all official documents using in Cambodia's government if you have noticed.

And of course, it is also a hardest one for other people who are not in government office as we are mostly not using Lunar calendar in private but when we need to use it, we always check Lunar calendar issued by corresponding organization.

Here is a help tool: https://tools.wikischool.asia/KhmerLunar

The tool helps for writing the correct date and in Khmer language.

If you find this useful and also want to continue engage with WikiSchool, reach them at facebook.

Updated (2021/02):

• The tool unpublished for sometimes being, be back, will inform.

Tools That Will Help Writer in Khmer

KhmerWriters.com is a new tool, provided by Danh Hong who is always providing the support for Khmer language in computing.

Danh Hong was also the one who handle khmerocr.org which is now no longer maintenance and the domain is listed on sale already but this time, he comes again with another tool that will be very helpful for Khmer writers who mostly face issue such as: wrong Khmer spelling, typing without zero space (ZWSP).

Khmer Spelling Checker (with Auto correction)

You can just pass the text and click on check spelling (ពិនិត្យអក្ខរាវិរុទ្ធ) then click on the next buttn for auto correction (កែដោយស្វ័យប្រវត្តិ).

Auto Zero Space

The next action, you need to aware for Khmer writing is to provide zero space to handle justify alignment and well line breaking. Just click put ZWSP as on the screen, then you can check the result by passing to your word document, you will see the different as following:

Of course, when you use it some words might not well detected, this require more corpus to put at his side, so hope it will be soon more accurate but at this stage, you can also use.

Let's try and see, let me know in comment for your thought.

Do you think is it helpful for you?
If you find it's helpful, please also consider to donate to Danh Hong's team to continue his work.