Download Text Recognizer app for android 2022 (OCR)

v1.0

Text Recognizer app uses machine learning APIs to instantly scan and extract text from images.
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4.5/5 Votes: 2
Developer
Shazad Anjum
Version
v1.0
Updated
September 17, 2022
Requirements
4.1 and up
Size
10MB
Get it on
Google Play

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Description

Text Recognizer app Review

Contents

Text Recognizer app uses machine learning APIs to instantly scan and extract text from images.
Convert your phone into a text scanner using this app. This app enables you to perform OCR (Optical character recognition) on your phone and allows you to easily scan text from images. Text Recognizer is a free OCR app to scan text from your images.

What is the Text Recognizer app?

The OCR technology analyses any image or document and then the Text Recognizer app compares it with all the fonts that have been fed into its database by matching particular features of a font typical to its characters.

A few of the OCR-driven software also process it through a spell checker so that unrecognizable words could be guessed by the image-to-text converter app. While it is less accurate, the most accurate approximation is what is required from the Text Recognizer app.

OCR software can provide a helping hand to researchers, students, as well as companies, and professionals.
Optical Character Recognition, is a powerful tool for bringing information from our analog lives into the increasingly digital world.

This technology has long seen used in building digital libraries, recognizing text from natural scenes, and understanding hand-written office forms. By applying OCR technologies, scanned or camera-captured documents are converted into machine-editable soft copies that can be edited, reproduced, and transported with ease.

Mobile OCR engine turns a smart phone into a document scanner, converts scanned documents from camera or photo album into regular text, and works in offline mode. Work on the general problem of camera-based text and document analysis can be categorized in several ways, by the type of device used, by the application, or simply by the type of text processed.

Different Mobile based OCR platforms are available today to convert image text into an editable format. Mobile OCR systems work either online or offline and are available to recognize
handwritten and typed text.

Online OCRs are usually cloud-based OCR platforms that send an image out to their server, process the image, and send back the text on the image in a computer-editable format

The major use of OCR scanner apps lies in converting paper documents into editable softcopy. Before the invention of OCR, paper documents had to be re-typed in case there was an error, a strenuous and time taking task.

This Text Recognizer app also find a massive use in digitizing historic documents, automatic vehicle plate identification, data entry and aiding visually impaired in reading.

Features of Text Recognizer OCR:

1. OCR from images
2. Scanned images history
3. Edit, delete, copy and share the scanned text

Text Recognizer’s OCR feature supports over 100 languages. The language in your images is detected automatically.

In recent years, several mobile OCR applications have been introduced to the market to enable quick text access. The increasing availability of high performance, low priced, portable digital imaging devices has created a tremendous opportunity for supplementing traditional scanning for document image acquisition.

Digital cameras attached to cellular phones, PDAs, or as standalone still or video devices are highly mobile and easy to use; they can capture images of any kind of document including very thick books, historical pages too fragile to touch, and text in scenes; and they are much more versatile than desktop scanners.

Traditional scanner-based document analysis techniques provide us with a good reference and starting point, but they cannot be used directly on camera-captured images. Many researchers worked for the development of mobile based OCR Systems.

In this Text Recognizer app, Camera captured images can suffer from low resolution, blur, and perspective distortion, as well as complex layout and interaction of the content and background.

In this paper we begin by describing typical imaging devices and the imaging process and present a survey of applications for recognizing documents captured by digital cameras.

Conclusion

Hand-held devices allow user to capture images from arbitrary locations and distances that are impractical for scanners. With recent widespread applications of computer and multimedia technologies, demand in creating paper less environment is increasing.

Automatic procurement from documents become an active research area, as much knowledge is acquired from documents such as technical reports, government files, newspapers, books, journals, magazines, letter, etc.

The manual acquisition of knowledge from such documents can involve an extensive amount of handcrafting. Such handcrafting is time-consuming and very laborious.

most of the available systems work for European scripts and very few mobile applications are available to recognize Indian scripts. The challenges of complex content and layout, noisy data, and variations in font and style keep the field active.

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