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Case Study - Optical Character Recognition (OCR)

Business Problem

In today’s world, every company needs to go for digitization to keep up with changing government taxation and regulation needs. One problem is encountered when the company still relies on handwritten or typed invoices. This may create problems when the company is trying to assess its business strategy in light of the past value derived from its business. It may also be a bother to manually enter the invoices into a computer.

Possible Solution

When you have to write multiple business documents that are written in the hand-written form then it might take hours or even some days. Here, Optical Character Recognition (OCR) can help the writers to convert the hand-written document into the digital form within seconds.

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You just need to scan the document and upload the image to the tool while the rest of the work will be done by the tool. Through scanning, the OCR tool will automatically generate the editable text and you can modify it according to your needs. In business, most of the time, the management team might write the material in the hand-written format but through the OCR, it can easily be converted into an editable format

Outcome

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Optical Character Recognition (OCR) takes handwritten or scanned characters as input and digitizes them so that they are available in electronic form. We have devised a tool using OCR that takes in a handwritten or scanned document as input and outputs the text in an electronic form.

For example, you are writing a policy paper that is of multiple pages and you missed a policy then it can create a big issue for your company. In this sense, you should use the OCR that has better accuracy. The OCR although don’t have perfection but still can cover up the human errors.

When you are writing with the help of OCR technology there are fewer chances of human errors. Humans usually type the content with a faster speed to cover more content in less time. During this, typing and spelling mistakes are usually common and this can create a problem for the business.

With the involvement of artificial intelligence, you can easily make your content accurate as the AI-based tools can solve your grammatical and spelling errors. It is recommended to proofread your content after you convert the file with the OCR tool.

CASE STUDY - eBooks

Business Problem

Today, there are many apps where you can read classic books in electronic form. You don’t need to borrow a book either manually or digitally. So how do these apps or platforms get the classic texts converted to electronic form. That is the business problem they face. Usually, the apps now a days hire people to type the classics content into a word processor programme so that the texts can be obtained in an electronic form.

Problem Description

The problem is how to convert handwritten or scanned classic books to electronic form where the text can be used in any form as per the user’s intent. Users like to apply different colours and different fonts to the text characters and that is only possible if the characters are in electronically editable format. Of course, accuracy of the characters converted to electronic form is a concern. But the solution has to be technologically advanced to take care of this accuracy problem.

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Possible Solution

Optical Character Recognition (OCR) programs can take handwritten or scanned books as inputs and output electronic characters which are editable. A good image to text tool can read images from any image format like PNG, JPG, BMP, GIF, JPEG and TIFF. Image to text tool can convert scanned images to text, an official document, a screenshot of a web page, or any random image containing some characters.

Outcome

We have designed an image to text converter tool which can take any image format and convert characters to electronically editable form. The demand for pulling text from images is on the rise because of the upward trend of using multimedia in education, eCommerce, finance and other businesses.

Image to text tool offers multiple language support. Apart from uploading options, an image can be converted to text by pasting the URL of the image in the URL box. This feature is very useful when you are surfing the internet and come across an image that includes text.

We have come up with unique and in-demand features that make it convenient for our users to perform photo search and obtain the text from it. The text extractor can take out text from low-resolution and blurry images as well. There is no need to waste your time typing all the text from pictures by yourself.

The books apps can use this tool to convert the scanned classic texts to electronic form.