Last Updated on December 1, 2022 by Sourav Sahu
Despite the revolution of technology, businesses still depend on preparing papers type documents to use in multiple tasks. However, making amendments to the documents is considered a problem.
For this reason, many businesses hire data entry workers to make amendments to documents. But this task is very time taking and also so costly.
This task seems to be easy but it requires a lot of time when manual data entry is needed. This is why now businesses are using the OCR technology that converts the word extractor from image documents by scanning the text from images.
The word extractor from the image is an online tool that is used for extracting the text from images and turning that text into a new document within no time.
What is OCR Technology: How does it Work?
OCR is known as optical character recognition and is a part of advanced technology. This helps you to get the text that you can edit by scanning the images.
The reason for it that why the accurate image-to-text converter online technology is used is to eliminate the physical need to transform the text from images.
In the early times, the OCR technology is just capable of converting the word extractor from the image to a particular type of text font. But the modern-day OCR technology is able to turn the images that contain various types of text.
The modern OCR is based on advanced algorithms, which work on analyzing the text patterns contained in an image. After the text analysis, the pic-to-text converter extracts the text and displays the text from pictures to a text document that is editable.
To get the best output from the OCR tool scan the document in a clear form. When the image is blurred, then the result of the image to text might get affected.
Ways to Extracting Text from Images:
Below are some of the ways that can be used to turn the text out of images.
Use an Online Image to Text Converter:
Many web portals & OCR word extractor from the image tool allows you to turn pictures into textual documents without installing any specific software or plugin.
All you need is to open the image scanner online and upload the image that you want to turn into the text. The best part of this tool is that you can access it on any device. The procedure of text extraction is quite simple and fast.
After uploading images into the tool, you are required to click the convert button. As a result, the OCR turns the text from the picture and displays the editable text within fractions of seconds.
Extract Text with Google Docs:
Google doc is another incredible way of turning the word extractor from images. Google doc has a built-in feature of OCR technology, which converts the images to text within the blink of an eye.
This facility of document creation is utilized by millions of people across the globe. For the extraction of text, you are required to open Google Drive.
Once you log in to Google Drive, then you will see documents, images, and some other files you saved. If the image you want to use for text extraction, then simply right-click the image & select the google doc option from the open with option.
When you click the image, then it will be accessed by the docs & text extracted from images will be in front of you.
Why is OCR (Optical Character Recognition) Important?
Many businesses receive information from print media. Invoices, paper documents, printed contracts, and scanned legal documents are some examples of business processes.
The large volume of paper documents consumes much time and space to store and manage them. Paperless document management is a way to get rid of this issue.
This process needs manual intervention, which is tedious and slow as well. This is where image-to-text OCR technology comes into the picture.
This technology not only transforms the image text into an editable text but the word extractor from the image also saves your precious time.
Digitizing the documents creates the picture files along with the hidden text within the files. Texts of the images can’t be processed by the software as text documents.
Jpg to text converter solves this issue by transforming the text of the images into editable text that can also be analyzed by other software. This text then can also be used to conduct analytics, and operations, automate, streamline, processes, and improve productivity also.
What are the Benefits of OCR?
Following are some of the major benefits of OCR.
Businesses are converting their existing as well as new documents into completely searchable knowledge archives. They process the text database by utilizing the OCR tools for further knowledge processing.
Artificial Intelligence Solutions:
The OCR image-to-text is a part of the other AI solution, that businesses may utilize. For instance, it scales & reads a number of plates & road signs for the self car driving, detects the logo from social networking posts, etc.
This optical character recognition assists businesses to make better marketing & operational decisions. This will not only reduces expenses but also improves the customer experience as well.
This is the major reason why the word extractor from image technology gained huge hype.
OCR or image-to-text technology proved itself a very promising and helpful technology. It allows you to convert the text on images to editable text for further use.
People at workplaces now don’t require to type text, as the png to text converter offers the detection of handwritten text and displays text that a machine can understand.
OCR technology is a perfect choice for businesses for automating text extraction from printed to written text via scanning images and converting them to text a machine can understand for data processing.
How does image text extraction work?
Image text extraction is a process of extracting text information from images. This can be done using a number of different methods, including optical character recognition (OCR), deep learning, and feature extraction.
What is the process of extracting information from the image?
There are a few different ways to extract information from an image. One way is to use feature detectors, which look for specific features in the image and extract data from them. Another approach is to use the watershed algorithm, which tries to find areas of the image that differ in color or brightness.