The world has drastically changed in recent years regarding technology and the internet. We are now sharing all our documents via the internet instead of sharing them in paper format. Mostly, people share their concerned documents in picture format. Have you ever faced a problem with text editing of any picture? If yes, you must have searched for ways to extract text from image to get the text in editable format. Do you want to know about a specific technology that can help you in this regard?
This blog will show you how a specific technology named text recognition technology can help you in this regard. Just keep reading to have a better idea about this technology in detail.
What is Text Recognizing Technology?
It is a particular technology that aims to recognize text from any scanned image or document and extract it to make it editable. Text recognition is a sub-category of OCR technology that mainly works on the combination of two technologies.
This technology is not the one that has been introduced recently. But it has a prominent history of around 100 years in different fields. With extra internet usage, it has become popular, and thousands of people are using it.
According to research, the market value of this technology is around $10 billion. It shows how popular and useful this technology is. But the major proportion of this technology is in the image to text extraction process.
Do you want to know how it will help you in doing so? Well, let us explain it in the following section step by step.
How does Text Recognition Technology Help in Text Extraction from Images?
If you use a tool to extract text from image, here are the steps that usually take place at the backend.
Depending on the software you’re using, the whole process can take some seconds to complete or a couple of minutes.
The first step in text recognition technology is image pre-processing. It involves several techniques that include the De-skew method in the initial stage.
When the image captures, the text recognition technology aligns the image in a proper direction. It either tilts the image counterclockwise or clockwise to create horizontal or vertical lines.
After the De-skew technique, the text recognition technology removes positive and negative spots from the image to smooth its edges.
It converts the image into a black-and-white color pattern with the help of the Binarization method. It helps to differentiate characters in black from the background in white to recognize patterns in the image.
In the layout analysis, the text recognition algorithm identifies tables, columns, and paragraphs. Although, this stage is practical when the image has multi-column layouts and tables.
In this step, the shape of characters and words are baselined. The script will transform at the word level if there is a multi-language document. Well, the multiple linked characters are divided and broken into single characters.
Finally, the image pre-processing concludes with the normalization process, where the aspect ratio and scaling of the scanned document are performed.
Text recognition technology follows two different methods to extract text from images.
- The first method allows the algorithm for feature detection to define a character by analyzing its lines and strokes.
- The second method works under pattern recognition to identify the whole character.
In the post-processing step, the finalization of characters and letters gives the whole output. Furthermore, the correction of spelling and grammar errors will also fix in the post-processing stage if made by the text recognition technology.
Text recognition technology is the product of modern-day technology. It has influenced the academic and marketing departments to transform document management methods. With the help of image recognition technology, the manual process of writing text from images has become much more manageable.
This article discussed how text recognition technology helps to extract text from images. We discussed the complete process to define how this technology works precisely. We hope this article was informative for you to understand the working of text recognition technology.