Tesseract Ocr Online

1. Tesseract Ocr Engine
2. Tesseract Ocr online, free

Free Online OCR Convert JPEG, PNG, GIF, BMP, TIFF, PDF, DjVu to Text About NewOCR.com is a free online OCR (Optical Character Recognition) service, can analyze the text in any image file that you upload, and then convert the text from the image into text that you can easily edit on your computer.

An Easy-to-use OCR Program — ApowerPDF

First and foremost, we recommend ApowerPDF. This is a PDF tool offering the OCR function allowing you to scan PDF files and convert them to an editable format. Moreover, it supports numerous languages such as English, French, German, Italian, Korean, Japanese and so on. Aside from that, users can change the page range wherein they can choose all pages or pick pages that want to convert. In just a few clicks, your PDF file will be editable.

Click 'Choose File' button to select a file on your computer. You can also click the dropdown button to choose online file from URL, Google Drive or Dropbox. When using default OCR engine, the source file format can be JPG, PNG, GIF, BMP or TIFF. The output file format will be TXT. VietOCR Description: A Java/.NET GUI frontend for Tesseract OCR engine. Supports optical character recognition for Vietnamese and other languages supported by Tesseract. Tesseract.jsis a pure Javascript port of the popular Tesseract OCR engine. This library supports more than 100 languages, automatic text orientation and script detection, a simple interface for reading paragraph, word, and character bounding boxes. Tesseract.js can run either in a browserand on a server with NodeJS.

Price: $29. 95

Other OCR Software to Extract Text from Scanned PDF

ABBYY FineReader

ABBYY is an OCR software for Windows 10 that can recognize characters from the PDF file. It offers both online and desktop versions. In that case, you can work with your PDFs using your desktop or laptop. Moreover, it can recognize texts from more than 190 languages from scans and photos. Besides that, the documents can be stored in the cloud for up to 14 days.

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Readiris

Readiris is an OCR solution that can be utilized on Windows. This software enables you to change the text from the scanned images without causing any trouble. Furthermore, it is capable of recognizing text from multiple PDF files with its batch processing feature. Apart from that, it supports saving files as several output formats. Lively logic 1 4 2 download free.

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Free Online OCR

An alternative OCR program that can extract text from the PDF and images to convert it into an editable file is Free Online OCR. As its name implies, this a free online OCR tool that can be used on most of the browsers. Two things you should note however, it enables you to convert 15 files per hour without requiring you any registration with its guest mode. Second, it only allows you to upload files of up to 15MB.

Price: Free

Capture2Text

The next tool we have is Capture2Text. This is one of the best OCR software programs great for extracting text from image files conveniently. With this OCR program, users just need to press the Windows key + Q to OCR capture. Furthermore, it is very easy to use since users just need to screenshot the part they wish to convert and then copy the text after. You can use the hotkey 'Windows Key + Q' to capture the screen easily.

Price: Free

Free OCR Software

This software can be used on Windows. This software includes a convenient Windows installer. Aside from that, it uses the latest Tesseract OCR engine which recognizes more than 100 languages. It is completely compatible with Windows 7, 8, Vista and XP.

Price: Free

SimpleOCR

Another free tool is SimpleOCR. With it, you can scan without experiencing any delay. This tool is 99% accurate and 100% free. With this tool, you can accurately convert the document into an editable format. Apart from that, if you have several files that need to be converted, you can use its batch OCR function.

Price: Free

Boxoft Free OCR

Last OCR program recommened is Boxxoft Free OCR. This is a handy tool that can be used to extract text from image files. In that case, you can conveniently scan documents and turn them into an editable format. Furthermore, it supports multiple languages including English, Italian, German, Spanish, French, Portuguese, Dutch, and so on.

Price: Free

Table of Comparison

Conclusion

As shown above, these are the best OCR software that you must try. Here, we listed both paid and free tools that you can utilize depending on your needs. If you want to save money, you can use the free tools. While on the other hand, use a paid version if you want an advanced OCR function and other PDF tools. In that case, ApowerPDF best fits since it has everything you need in PDF software.

In today's post, we will learn how to recognize text in images using an open source tool called Tesseract and OpenCV. The method of extracting text from images is also called Optical Character Recognition (OCR) or sometimes simply text recognition.

Tesseract was developed as a proprietary software by Hewlett Packard Labs. In 2005, it was open sourced by HP in collaboration with the University of Nevada, Las Vegas. Since 2006 it has been actively developed by Google and many open source contributors.

Tesseract acquired maturity with version 3.x when it started supporting many image formats and gradually added a large number of scripts (languages). Tesseract 3.x is based on traditional computer vision algorithms. In the past few years, Deep Learning based methods have surpassed traditional machine learning techniques by a huge margin in terms of accuracy in many areas of Computer Vision. Handwriting recognition is one of the prominent examples. So, it was just a matter of time before Tesseract too had a Deep Learning based recognition engine.

In version 4, Tesseract has implemented a Long Short Term Memory (LSTM) based recognition engine. LSTM is a kind of Recurrent Neural Network (RNN).

Version 4 of Tesseract also has the legacy OCR engine of Tesseract 3, but the LSTM engine is the default and we use it exclusively in this post.

Tesseract library is shipped with a handy command line tool called tesseract. We can use this tool to perform OCR on images and the output is stored in a text file. If we want to integrate Tesseract in our C++ or Python code, we will use Tesseract's API. The usage is covered in Section 2, but let us first start with installation instructions.

1. How to install Tesseract on Ubuntu and macOS

We will install:

1. Tesseract library (libtesseract)
2. Command line Tesseract tool (tesseract-ocr)
3. Python wrapper for tesseract (pytesseract)

Later in the tutorial, we will discuss how to install language and script files for languages other than English.

1.1. Install Tesseract 4.0 on Ubuntu 18.04

Tesseract 4 is included with Ubuntu 18.04, so we will install it directly using Ubuntu package manager.

1.2. Install Tesseract 4.0 on Ubuntu 14.04, 16.04, 17.04, 17.10

Due to certain dependencies, only Tesseract 3 is available from official release channels for Ubuntu versions older than 18.04.
Luckily Ubuntu PPA – alex-p/tesseract-ocr maintains Tesseract 4 for Ubuntu versions 14.04, 16.04, 17.04, 17.10. We add this PPA to our Ubuntu machine and install Tesseract. If you have an Ubuntu version other than these, you will have to compile Tesseract from source.

1.3. Install Tesseract 4.0 on macOS

We will use Homebrew to install Tesseract on Homebrew. By default, Homebrew installs Tesseract 3, but we can nudge it to install the latest version from the Tesseract git repo using the following command.

1.4. Checking Tesseract version

To check if everything went right in the previous steps, try the following on the command line

And you will see the output similar to

2. Tesseract Basic Usage

As mentioned earlier, we can use the command line utility or use the Tesseract API to integrate it in our C++ and Python application. In the very basic usage, we specify the following

1. Input filename: We use image.jpg in the examples below.
2. OCR language: The language in our basic examples is set to English (eng). On the command line and pytesseract, it is specified using the -l option.
3. OCR Engine Mode (oem): Tesseract 4 has two OCR engines — 1) Legacy Tesseract engine 2) LSTM engine. There are four modes of operation chosen using the --oem option.
4. Page Segmentation Mode (psm): PSM can be very useful when you have additional information about the structure of the text. We will cover some of these modes in a followup tutorial. In this tutorial we will stick to psm = 3 (i.e. PSM_AUTO).

   Note: When the PSM is not specified, it defaults to 3 in the command line and python versions, but to 6 in the C++ API. If you are not getting the same results using the command line version and the C++ API, explicitly set the PSM.

2.1. Command Line Usage

The examples below show how to perform OCR using tesseract command line tool. The language is chosen to be English and the OCR engine mode is set to 1 ( i.e. LSTM only ).

2.2. Using pytesseract

In Python, we use the pytesseract module. It is simply a wrapper around the command line tool with the command line options specified using the config argument. The basic usage requires us to first read the image using OpenCV and pass the image to image_to_string method of the pytesseract class along with the language (eng).

2.3. Using the C++ API

In the C++ version, we first need to include tesseract/baseapi.h and leptonica/allheaders.h. We then create a pointer to an instance of the TessBaseAPI class. We initialize the language to English (eng) and the OCR engine to tesseract::OEM_LSTM_ONLY ( this is equivalent to the command line option --oem 1) . Finally, we use OpenCV to read in the image, and pass this image to the OCR engine using its SetImage method. The output text is read out using GetUTF8Text().

You can compile the C++ code by running following command on terminal,

Now you can use it by passing the path of an image

2.4. Language Pack Error

You may encounter an error that says

It just means the language pack (tessdata/eng.traineddata) is not in the right path. You can solve this in two ways.

1. Option 1 : Make sure the file is in the expected path ( e.g. on linux the path is /usr/share/tesseract-ocr/4.00/tessdata/eng.traineddata).
2. Option 2 : Create a directory tessdata, download the eng.traineddata and save the file to tessdata/eng.traineddata. Then you can direct Tesseract to look for the language pack in this directory using

   Similarly, you will need to change line 20 of the python code to

   and Line 18 of the C++ code to

3. Use Cases

Tesseract is a general purpose OCR engine, but it works best when we have clean black text on solid white background in a common font. It also works well when the text is approximately horizontal and the text height is at least 20 pixels. If the text has a surrounding border, it may be detected as some random text.

For example, if you scanned a book with a high-quality scanner, the results would be great. But if you took a passport with complex guilloche pattern in the background, the text recognition may not work as well. In such cases, there are several tricks that we need to employ to make reading such text possible. We will discuss those advance tricks in our next post.

Let's look at these relatively easy examples.

3.1 Documents (book pages, letters)

Let's take an example of a photo of book page.

When we process this image using tesseract, it produces following output:

Even though there is a slight slant in the text, Tesseract does a reasonable job with very few mistakes.

3.2 Receipts

The text structure in book pages is very well defined i.e. words and sentences are equally spaced and very less variation in font sizes which is not the case in bill receipts. A slightly difficult example is a Receipt which has non-uniform text layout and multiple fonts. Let's see how well does tesseract perform on scanned receipts.

1 Items Subtotal 1.99
Tax .15

Total 2.14
*xMASTER* 2.14
MASTER card * #XXXXXXXXXXXX548S
Apo #AA APPROVAL AUTO
Ref # 05639E
Entry Method: Chip

3.3 Street Signs

If you get lucky, you can also get this simple code to read simple street signs.

BICYCLE RIDING

ROLLER BLADING

Tesseract Ocr Engine

SCOOTER RIDING
®

Note, it mistakes the screw for a symbol.

Let's look at a slightly more difficult example. You can see there is some background clutter and the text is surrounded by a rectangle.

Tesseract does not do a very good job with dark boundaries and often assumes it to be text.

However, if we help Tesseract a bit by cropping out the text region, it gives perfect output.

Tesseract Ocr online, free

The above example illustrates why we need text detection before we do text recognition. Ishowu studio 2 2 15. A text detection algorithm outputs a bounding box around text areas which can then be fed into a text recognition engine like Tesseract for high-quality output. We will cover this in a future post.

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