Document Segmentation and Language Translation Using Tesseract-OCR

Sahil, Thakare; Kamble, Ajay; Thengne, Vishal; Kamble, Usha R.

doi:10.1109/iciinfs.2018.8721372

Cited by 21 publications

(6 citation statements)

References 3 publications

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“…the json responce the ocr image function processimage().json . Aim of Tesseract was to recognizes white on black which help to analysis and recognizes a particular character [10]. The data cleaning process get more complex when data come from some heterogeneous source, these problem has been solved by data cleaning and data transformation, data cleaning modules such as removing columns with less data removing unnecessary rows identifying some valuing and feeling it is done by Python code with the help of machine learning algorithm , most of the data got missing after cleaning then to overcome this used pyspellchecker , Text-blob and Auto-correct [1], this all are open source packages that allow to correct and check spelling , meanwhile by using Text-blob allows us to use custom database it provide simple api for divining into natural language processing(NLP) job…”

Section: A Image Scanningmentioning

confidence: 99%

File Conversion Application using Kivy and Tesseract – OCR

More¹,

Jain²,

Kanakia³

2021

IJAEMS

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In the fastest developing world education is the most important factor in all over the country. Indian Rural teachers have a great responsibility on their shoulders to educate the students without getting technological support. They face various challenges like network problems, lack of technical skills, the burden of multitasking. In this research, paper researchers try to make an application for Indian rural teachers to fight technical challenges and overcome the burden on them.

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Section: A Image Scanningmentioning

confidence: 99%

File Conversion Application using Kivy and Tesseract – OCR

More¹,

Jain²,

Kanakia³

2021

IJAEMS

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“…Setelah gambar kartu nama selesai melalui proses preprocessing, maka gambar akan dilanjutkan ke proses ocr memanfaatkan tesseract [9]. Proses ocr pada Penelitian ini akan memanfaatkan library pytesseract dan mengikuti pendekatan pada [10] dan [11]. Sebelum melalui proses ocr, gambar yang sudah mengalami preprocessing akan dibagibagi sesuai kontur yang ada seperti pada Gambar 27.…”

Section: Pengenalan Karakterunclassified

Sistem Manajemen Kartu Nama dengan OCR dan Ekstraksi Informasi Otomatis

Darmawan

Nasuha

Zaman

et al. 2021

INSYST

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Sebagai pelaku bisnis, kartu nama adalah salah satu hal yang penting untuk bertukar informasi. Namun kartu nama biasanya mudah hilang atau rusak, sehingga beberapa orang biasanya menyimpan informasi dari kartu nama itu pada telepon genggam atau komputer mereka. Penelitian ini akan membuat sistem manajemen kartu nama baik individu dan juga perusahaan dengan ekstraksi informasi kartu nama otomatis untuk mempermudah pengguna perorangan ataupun perusahaan dalam melakukan penyimpanan kartu nama para kolega. Untuk mewujudkan aplikasi yang dilengkapi dengan fitur tersebut dilakukan proses pengenalan karakter pada gambar kartu nama menggunakan Tesseract OCR dan information extraction memanfaatkan klasifikasi entity dengan membangun classifier menggunakan Naive Bayes dan mengkombinasikannya dengan rule based. Hasil uji coba yang telah dilakukan mendapatkan performa 85.1% untuk pengenalan karakter dan 86% untuk pengklasifikasian entity. Dilakukan juga uji coba fungsionalitas terhadap setiap fitur pada sistem ini dengan menggunakan metode blackbox testing yang memastikan setiap aksi yang dilakukan pengguna akan menghasilkan output sesuai target yang diharapkan. Selain itu, dari hasil kuisioner yang berisikan tentang usability dari sistem ini, sebagian besar responden merasa terbantu dalam memanajemen kartu nama dengan menggunakan sistem aplikasi ini.

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“…Tesseract is a tool recognizes and reads the text present in images as in Fig. (3) where the algorithm is applied to the image of the energy meter to extract the meter reading where this process is done in four stages, in the first stage converts the image to grayscale so as to reduce the image details and then in the second stage of the image is converted to a binary image to reduce and remove the background details and in the third stage, it is the corrosion process to reduce and eliminate noise in order to isolate the number from the background in order to facilitate the process of distinguishing numbers [9][10].…”

Section: Raspberry Pi3 Module Bmentioning

confidence: 99%

Design and Implementation of a Prototype Automatic Reading System for the Consumers’ Electrical Energy Meters

alsoufi¹,

Alneema²

2020

(AREJ)

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The research aims to design and implement a prototype for an automated system that reads electrical energy meters for the consumers and collects these readings in a central unit via the World Wide Web (the Internet). This is done by adding a camera that automatically captures the meter reading of the electric meter as an alternative to the mobile meter reader. This meter reading image is processed and the value of the meter reading is extracted by using a Raspberry Pi device and the Python language depending on OCR (Optical Character Recognition) algorithm and then sent via Internet and collected from all consumers through the Internet cloud in a database in the Central Electricity Department. After collecting this information, it can be used to monitor electrical loads, record invoices, and give reports about loads and costs to consumers, and thus participate in rationalizing electrical energy consumption. The most important characteristic of the proposed model is its simplicity as it does not change anything in the structure of the meter and does not need to make any modifications to its internal composition. This system will save a lot of effort and time and contribute to reducing human errors when reading metrics and making some kind of interventions between the supplier and the consumer to reduce waste, rationalize consumption and reduce costs.

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Document Segmentation and Language Translation Using Tesseract-OCR

Cited by 21 publications

References 3 publications

File Conversion Application using Kivy and Tesseract – OCR

File Conversion Application using Kivy and Tesseract – OCR

Sistem Manajemen Kartu Nama dengan OCR dan Ekstraksi Informasi Otomatis

Design and Implementation of a Prototype Automatic Reading System for the Consumers’ Electrical Energy Meters

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