Do you wish to turn blurry images into editable text? Follow along and find out how:
Many a time, businesses require scanning of documents that aren’t in their primary shape. The practice of turning such physical texts into virtual is becoming more and more common as we speak. Because it’s not only limited to businesses, as common people require this just the same.
That’s when OCR technology steps in and helps them turn their valuable paperwork into virtual data. The common uses of this practice are:
- Improved work efficiency
- Easy data automation
- Assistance in studying
- Assistance in writing
- Storing valuable text in virtual clouds
These all sound great until you run into a blurry text. So, can you extract text from an image that’s not precisely visible? Yes, you can, with OCR. Therefore, let’s dive in and find out what OCR is and how it extracts text from images—even the blurry ones.
Using OCR (Optical Character Recognition)
Using Optical Character Recognition isn’t a difficult task. In fact, it’s one of the easiest things you can do to extract text from your images. It employs various elements, such as:
- File upload – drag & drop
- Image scan and conversion through NLP
- Using AI to read crude or uneven texts
- Converting the extracted data into editable text
(Also Read: How OCR Technology Can Ease Your Writing Process?)
So, just how does it all work? Here’s a demonstration using Ocronline.info:
· Image Upload
The first step is to upload the image from which you wish to extract the text. It’s a straightforward process and doesn’t require anything extra. Here’s what you see upon visiting Ocronline.info
You can click on “Select Image” and browse your computer for the desired file. Or, you can drag and drop the image in the marked section, just like we did here:
Here you can notice the image is ready to be scanned now. So, let’s move to the next step:
· Scan & Extraction
This is the step where your text will be extracted by the program. The tool will be using various technologies, from OCR to IWR & ICR (we’ll explain that in a bit). So, now all you need to do is click on get text, as marked here:
As mentioned before, upon dragging and dropping the files here, the text is ready for extraction. Now, all we need to do is let the tool do its work after we click on the marked button.
· Editable Text
Now that the image has been pasted and the tool has been instructed to extract the text, here’s what you will see next:
We used a really difficult picture to read, as you can see here. However, the tool has recognized 95% of the words in it. For instance, the term “piniple” must be “principle.” Those are the kind of minor mistakes you can easily fix.
( Checkout : How Does Optical Character Recognition (OCR) Work?)
How Does OCR Do That?
As seen in the demonstration above, the tool can help you extract text from any image. But, how exactly does it do that? Here are three main technologies used by OCR tools like Ocronline.co:
(See Also: How Does Optical Character Recognition (OCR) Work?)
· IWR (Intelligent Word Recognition)
Intelligent Word Recognition or IWR is the primary form of OCR today. It takes elements from both OCR and AI to execute any text extraction.
Instead of relying on an optical lens, this technology thoroughly recognizes shapes on a paper. This allows the tool to capture words entirely, including typed and handwritten words.
· ICR (Intelligent Character Recognition)
ICR or intelligent character recognition is more or less the same as IWR. However, instead of capturing words, it focuses on capturing characters.
This tech is at the forefront of reading handwritten or blurry images. It tries to make sense of each character present on a paper. This allows the tool to capture blurry images efficiently.
· OWR (Optical Word Recognition)
OWR or Optical Word Recognition uses old-school methods to capture and extract text from images. This tool is ideal for capturing images from type-written or scanned images. Mainly because it’s made to recognize machine-written words instead of handwritten ones.
Using An OCR Tool With IWR To Capture Text From Blurry Images
Now that we know the intricacies of such tools let’s talk about how OCR Online can help you capture text from such images. So, let’s dive right into it:
· Upload The Blurry Image
The first step is to upload the image to the website’s tool section. You can either select image or drag and drop it here:
As you can see, you have the option to “Select Image,” or you can drag and drop your image in PNG, JPG, GIF, or SVG format. Once you do, here’s what it should look like:
As you can see here, we have uploaded the image with blurry text in it. This image has some parts visible, while one-half is entirely blurred.
· Let It Scan Your Text
Now, the next step is to let the tool do its job by scanning your text. The scanning animation will appear a little something like this:
This process takes up about 10-15 seconds, depending on the presence of text on your desired image.
· Use Editable Text
After around 10-15 seconds, you should be able to see the result like this:
As you can see here, the tool has successfully captured the text from the blurry image. This isn’t only made possible with basic OCR but also because of OCR Online’s state-of-the-art algorithms and usage of IWR. That’s why OCR Online is your best bet at capturing such images.
· Scan Again If Needed
As you can see in the text above, around 98% of the text is accurate, while the other 2% can easily be guessed. However, sometimes AI has difficulty reading such texts. So, what can you do?
Try scanning your desired image once more. By firing up the AI to read it once more, IWR might just recognize it on the second time. Therefore, just to be double sure, try to use OCR Online once more if the first time around isn’t enough.
This is how you can extract text from blurred images. All you have to do is use OCR Online according to the instructions above.
Danial is a New Jersey-based freelance writer with a background in Computer science, Machine learning and technology coverage. He completed a Master’s degree in Computer science at Harvard University.
He currently works as Content Writer for Ocronline.info.