However, it is true that they often struggle when a complex image or document is provided, as they solely operate on OCR algorithms. This raised the concern that additional approaches should be adopted to further improve the precision and effectiveness of current OCR tools.
To address this, there is likely no alternative more suitable than utilizing the power of Artificial Intelligence. There are numerous reasons behind this, and some of the major ones will be discussed in this blog post.
Reasons Why Artificial Intelligence Should Be Integrated into OCR Tools
Below we have discussed some of the major reasons why Artificial Intelligence technology should be embedded into modern OCR-based tools.
Handling Images with Diverse Elements
We are living in a digital world that is filled with images. Take your example, you will be sending and receiving several images daily that contain a mixture of plain text, special symbols, characters, or even mathematical equations.
So, when extracting data or information from such types of images, modern tools operating on a single technology (OCR) will struggle. They will either generate a working error to the user or come up with inaccurate editable text that may contain mistakes or missing information.
By integrating AI technologies like machine learning (ML), natural language processing (NLP), or deep learning (DL) into OCR tools this issue can be easily resolved. The AI technology will boost the tool’s ability to effectively comprehend diverse image elements and perform accurate data extraction as quickly as possible.
Better Image Preprocessing
Image preprocessing is one of the most important stages in text extraction. Here, the OCR tools perform different tasks on the input photo such as noise reduction, skew correction, and image enhancement to ensure accurate text extraction.
By integrating the power of artificial intelligence in such solutions, the image processing process can be easily improved. The technology will not only quicken the process but also elevate the overall efficiency.
This means that even in non-ideal scanning conditions, the AI-powered OCR tools can still perform extraction with significant accuracy.
Tackling Poor Quality Sources
Scanned or especially handwritten documents may contain issues like speckles, shadows, or incomplete characters due to poor scanning. Faxed and photographed papers introduce additional distortions. The same is the case with images, they become blurry due to poor capturing or low-lightened.
In such sort of situations, OCR tools' accuracy falls sharply, increasing the overall chances of inaccurate results. Here AI technology will come in as a rescue. When intelligent technologies such as natural language processing (NLP) are integrated, these allow the tools to effectively scan and text from blurred and dark images and documents.
Do you know? There are also AI libraries like Pillow, OpenCV, etc. that work to enhance image or document quality for ease of data extraction.
Extracting Text in Different Languages
Business professionals and international brands will find this point relevant, as they often have to deal with text images and documents in different languages. We all know that every language in the world has a unique syntax and character set. This is where the problem starts with modern OCR tools.
With the integration of AI, this problem can be easily solved, let us explain how. The models are trained on a dataset of multiple languages which gives them the ability to quickly analyze syntax and patterns and ultimately leads to accurate data extraction even from pictures and documents available in multiple languages.
Contextual Understanding
We all know that normal OCR-powered tools lack contextual understanding. This means that if you provide them with an incomplete textual image, they will also come up with the same text as the output. However, when AI technologies like NLP are integrated into such tools, they will gain contextual understanding.
No matter if your input image’s text is complete or contains grammar or spelling errors, the AI-backed OCR tool will analyze the overall context and automatically make adjustments to provide 100% accurate output results.
Adaptive Learning
This is something that most of you will find interesting. Currently, the OCR tool simply scans and extracts the text from the given image and source. They don’t just learn from their generated output just like popular AI tools.
To provide them with this capability, these must have to be paired with artificial intelligence technologies. It will allow them to continuously improve their extraction performance and capability by analyzing past mistakes and difficulties.
Additionally, pairing OCR tools with AI technology will also help them get used to different image and document types, indicating maximum efficiency.
Increasing Overall Speed:
Finally, this is yet another reason why optical character recognition should be paired with AI technologies. Modern tools solely operating OCR will most likely take more time when processing complex input for text extraction. Obviously, this waiting will make the user frustrated.
So, when AI is paired with optical character recognition algorithms, it will automatically give a boost to the working ability, allowing them to perform image or document scanning and extracting within seconds, and serve the user with output results.
After going through all these reasons, we believe you will now have an idea about why artificial intelligence should be integrated into OCR-based tools.
Example of a Modern OCR Tool
Till now, there are only a few tools that have integrated artificial intelligence technologies into their working functionality. We performed diverse research online and tested numerous OCR tools by providing complex inputs to determine whether they were operating on AI or not.
Gladly, we found a reliable image to text converter. To prove that our selection is wise, we are going to upload an image that is not only a little blurry, but also contains a mixture of plain text, special symbols, and numerical data on the tool.
Here is the input picture:
The output from the tool:
As you can see in the screenshot attached above, the image to text converter accurately performed text extraction. This is a clear indication that it is using a combination of both OCR and AI technologies.
End Note
Modern tools are no doubt good at extracting editable data from images or documents. However, whenever a little complex input is provided such as a low-quality picture, they start struggling. To resolve this, many experts have suggested AI technologies should be integrated into these tools. There are multiple reasons behind this suggestion, some of the major ones are covered in this blog.
Frequently Asked Questions
What is OCR technology?
Optical character recognition is pattern-based technology that effectively scans the letters and words that the input image or document contains. And then extract them in an editable format while ensuring the highest accuracy.
How does AI enhance OCR tools?
