How do Optical Character Technology Can Help to Extract Text from Pictures?

The world has seen so many technological advancements in a relatively short time. We are swiftly moving towards a completely digitized automated ecosystem where there will be no or minimal manual chores. One of those revolutionary technological advancements is the OCR (Optical Character Recognition) technology. The introduction of OCR has made it possible for people to convert data from physical files directly to digital files storable on servers and cloud storage platforms.

This technology takes the help of imagery to make it possible. Data available in the shape of paper files is first scanned using a camera lens to convert it into the form of imagery, and then the OCR technology does its work. If you are still unaware of this useful technology that takes help from AI, Deep Learning, and Computer vision, then you are missing out on an efficient and accurate way of transforming data from paper and image to text.

In this writing, we will elaborate on how the OCR extracts text from pictures and why you need to use it for your benefit. Further details are given below:

How does OCR Work in Image to Text Conversion?

It is worth mentioning that OCR requires an image of the text that should be extracted and converted to a digitally editable file. Hence, you need to use a camera lens and a reliable image to text converter for this purpose. First, you will use the camera lens to capture the image of data available in hard copy. Once you do it, you need to upload the image to the photo to text converter, and it will do the rest of the work with the help of OCR, which will be working in the background. Here we will outline various phases of the picture to text conversion with the help of OCR. 

Read on to learn more.

  • Scan

The first phase of the image to text conversion is the scan of the uploaded image. During this phase, the OCR works in the photo’s background to text converter to analyze the procured picture. Then, it identifies the featured text in the image. This process is done with the help of the recognition of lighter and darker areas in the frame. The lighter areas in an image are recognized as the background, and darker areas are considered text.

  • Preprocessing

As the name indicates, this phase is about preparing text for extraction and conversion. First, the procured image is optimized to ensure accurate recognition of characters featured in the image. Preprocessing of the text includes rectification of mistakes in the text using AI for accurate conversion. The edges of the frame are also cleared for this purpose. Spots are also removed from the scan of the image for clear results. The lines, boxes, and script is also determined to recognize the font style and language of the featured text in the image. Finally, the image is tilted (if required) to align it properly. Once all these processes are done, the text in the image is ready for the text recognition phase.

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  • Text Recognition

Text recognition is the most critical phase of the image to text conversion process. This process involves identifying and extracting text characters featured in the procured image. There are two methods for this purpose. One method is pattern matching, and the second one is feature extraction.

    • The ‘Pattern Matching’ method is effective for known font styles or typed scripts only. During this method, individual characters are scanned in the form of glyphs and matched with the glyphs available in the deep learning library. The scale of the glyph is also considered during the recognition of characters using this method.
    • The ‘Feature Extraction method is a relatively advanced and more effective method for text recognition. It allows the converter to recognize handwritten script as well. In this method, the features of the character, such as lines, loops, and crosses, are compared with the available scans to find the match. 
  • Post-Processing

The post-processing phase of the image to text conversion method using OCR technology is about converting scanned characters into a digitally editable text file. You can get this file as a TXT or DOCX file. The available data in the above formats allows you to easily search for the required information from the text. Moreover, you can edit or modify the text digitally and keep the data saved on cloud-based storage platforms or servers.

End Words!

We have discussed the working of OCR technology in the image to text conversion process. This technology can become a reason for the growth of your business. The quick conversion of data available in hard copy to digitally editable formats will allow you to enhance the productivity of your business. Moreover, you will be able to reduce expenses that will otherwise go into the manual photo to text conversion process through old-school data entry tasks.

Considering all these benefits, it is time for you to take the help of technology and use an efficient picture to text converter for easy conversion of information saved in hard copies to digital data. We hope this article will help you transform your working environment and harness the power of technology for the growth of your business. We wish you luck with the process.

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