Turning text inside an image into a document is something that has only become possible due to advancements in artificial intelligence (AI). To be specific, one particular aspect of AI which we call OCR or Optical Character Recognition enabled machines to understand text inside an image and convert it to an editable format.
Before this, there was no way to transcribe text from an image to a digital document other than doing it manually. However, with OCR, it is now possible for computer systems to understand that specific configurations of pixels (that’s what an image looks like to computers) are characters. Then they write those characters in ASCII or UNICODE (whichever they support) which is the format used in digital documents.
Thanks to the ease and accuracy of these tools, they have an application in various fields such as data science, data management, and more.
Today, the tools that can do this are called OCR tools or image-to-text converters. In this article, we will look at one such tool in particular; the text extractor by Editpad.
How Does Editpad Convert Your Images into Written Documents
We discussed OCR and how it enabled computers to recognize text. But we didn’t go into details. We will delve into that as we discuss Editpad and see how it implements OCR.
How Does OCR Work to Extract Text in Editpad
Let’s take a look at the process that happens when we extract text from image with Editpad. There are some distinct steps that take place and result in the extraction of text from an image. Let’s take a look at them.
1. Image Preprocessing
Preprocessing refers to doing something before processing it. In the case of text extraction from an image, it means doing something to the image itself. In Editpad, what happens is that the image is cleaned first.
Cleaning refers to removing all unwanted things from an image such as splotches, marks, and dust particles that reduce image quality. The OCR implementation of Editpad is intelligent enough to recognize and remove these artifacts from the image.
Once that is done, the next step is binarization. In this step, all the colors are removed from the image until only black and white are left. Typically, the background is black while the text is white. This makes the text easier to make out and recognize.
At this point, the preprocessing is over.
2. Text Extraction from Image
Once the preprocessing is done, the actual text extraction takes place. There are numerous techniques for extracting text from an image, Editpad uses the following two.
- Feature extraction
- Pattern recognition
In feature extraction, the system checks each character for specific features. For example, the letter “H” has the features of two vertical parallel lines intersected with a horizontal line. As long as this feature is present the letter will always be correctly recognized. This means that even handwriting and unorthodox writing styles can be reliably recognized and extracted.
As for pattern recognition that is much simpler. The system checks whether the character to be recognized has a matching pattern with one in its database. If there is a similar pattern available, the character will be recognized, if there are no matching patterns, then it won’t be recognized. The main advantage of using this type of extraction is that it is faster than feature extraction and works well with standard fonts.
By using both techniques, Editpad is able to extract text from an image reliably.
3. Post Processing
During post-processing, Editpad checks whether the text it has extracted is accurate or not. It checks whether the text makes sense or not. Some of the most common things it finds during this process are:
- Typos
- Incorrect word forms
If you are thinking about whether it is not able to distinguish between intentional mistakes (such as stylistic typos i.e. stylz instead of styles) and unintentional ones, then don’t worry. It can do so reliably.
Anyway, this results in a better, more accurate output with almost no errors. After this, the text is presented to the user in a word processor-friendly format.
Accuracy and Other Features of Editpad Image to Text Converter
Now, that we understand how Editpad works to convert your images into written documents, it is time to understand how accurate it is as well as other features.
Accuracy of Editpad
The accuracy can be measured by extracting some text with the tool. To measure the accuracy, we will extract both handwritten text and digital text. Let’s take a look at both examples.
Handwritten text
We used the following image of handwritten text.
Here is Editpad’s text extractor’s output.
As you can see, the text has been recognized perfectly, so we can say that handwriting can be recognized as long as it is legible.
Digitally Written Text
For this example, we used the following image with digitally written text in it.
This was the output that we got.
As you can see, the text was extracted perfectly. So, we can say that the Editpad image extractor is very accurate.
Other Features of Editpad
Some prominent features of the Editpad text extractor are as follows.
- Image uploader for input
- Downloading output as a Word file
- Downloading output as a compressed Zip file
- Uploading multiple images at once
Aside from these useful features, this extractor is completely free to use and does not require any registration. Therefore it is a highly accessible AI powered image to written document converter.
Conclusion
In this article, we saw how AI makes your images into written documents. We specifically saw the implementation of the Editpad text extractor and how it works. We also saw other features of this tool as well as tested its accuracy. We rate it a 10/10 and recommend you use it to make your images into written documents.