Ever thought about how computers can read text from images? That’s where OCR (Optical Character Recognition) comes into play. But hold on, why is it a bit tricky for computers compared to us, and why is OCR such a game-changer?
So, here’s the deal: Computers don’t look at pictures like we do. They see images as a bunch of colored dots on a grid. But with OCR, computers get a special ability. They can actually see that these dots make up letters and numbers. Once the computer figures out the letter, turning it into words in a document is a walk in the park! Cool, right? Now we will take a brief look at how OCR works.
Table of Contents
How Does OCR Work?
The entire process of OCR takes place in three major steps. They are called:
- Preprocessing
- Text Recognition
- Post Processing
Preprocessing
Preprocessing is the first step in which the image gets ready for OCR. At the start, the background and text are separated. Light parts are treated as the background and taken out, so only the dark text remains.
After that, the image is “cleaned,” and any extra spots and lines are erased. This careful preparation gets everything set for accurate Optical Character Recognition.
Text Recognition
The real deal begins once the preprocessing stage wraps up including text recognition. This step follows one of two techniques: pattern matching or feature extraction.
Pattern matching takes a simple approach by attempting to match shapes in the image with characters that are already known. This method shines when the fonts are clear-cut, but it becomes an issue when you are dealing with handwriting. In such cases, you can use image text conversion tool which helps you extract text easily.
On the flip side, we have the feature extraction technique, which demands more resources. It operates by comparing the elements of characters based on specific rules. For instance, if two parallel lines have another line cutting through them both, it gets flagged as an “H” character.
Although this approach is a bit slower, it can even identify handwritten content. So, there you have it: a glimpse into the fascinating world of making computers understand the text hidden within images.
Post-processing
The final step is post-processing, in which the extracted text is converted to a computerized file. It is also checked for spelling mistakes, such as “tke” instead of “the”. These mistakes are then corrected, and the output is provided to the user.
Fact: Once the OCR is done converting images to text, postprocessing steps often involve spell-checking and formatting adjustments to ensure the accuracy and readability of the final output.
Steps for Copying Text from an Image
These are a few simple steps that you can follow to copy text from an image.
1. Search for an Image to Text Converter
The first thing you need to do is to open a browser and in your preferred search engine, type the following words: “Image to text”.
The search results should show you some tools as the top results. It can look something like this:
Just click on any of the top results, as all of these tools are very similar. You can check out multiple image-to-text converters and stick with the one you like best.
For our example, we will use the image-to-text converter by imagetotext.info. It is the top-ranked tool for this keyword, so its quality is guaranteed.
However, you can select any image-to-text converter, by checking a few things that are listed below:
- Is it free?
- Is the UI easy to navigate?
- Does it have many features?
From these three things, you should decide which one matters the most and then choose the image-to-text converter that satisfies you.
2. Input Your Image into the Tool
The second step is quite simple. You need to provide the image from which you want to copy the text to the tool. Now some tools only have one input option, while others may have two or even three.
The image-to-text converter goes beyond that, as it allows you to input images in four ways:
- drag and drop images into the tool
- browse your device to choose an image
- provide a URL
- Import images from Google Drive.
You can use the method that seems most convenient to you and input your image into the tool. After that, all you need to do is to confirm your decision to get the text from the image.
3. Copy/Download the Output Text
After you have inputted the image, the tool will take a few seconds to process it and extract all the text from it. The time can vary depending on your internet speed, server load, and the size of the image.
This Picture to text converter shows the image alongside the extracted text, so you can see if there are any mistakes. Usually, if the writing in the image is using a digital font, then there are no mistakes.
However, if the text is written in an unconventional font, then there is a chance that some characters do not get recognized correctly.
The extracted text can be copied directly to a document, or you can download it as a separate file. The choice is up to you.
Now that you have the text from the image, you are free to use it however you wish.
Conclusion
These easy steps show how to use an image-to-text converter for extracting text. These converters work well with regular fonts but might struggle with fancy styles like graffiti or cursive handwriting. Luckily, you can find these tools online and use them on different devices whenever you want.
Photo-to-text converters can reliably extract text from images if the font used is not too out of the ordinary (such as graffiti, cursive handwriting, or very “noisy” text).
A lot of these tools are paid, and some are free – you need to pick the best one based on the above mentioned characteristics.
An efficient online tool will not only help you in extracting image text efficiently – it will save hours of your time.
Frequently Asked Questions
Answer: Image-to-text conversion, also known as OCR, involves teaching computers to understand the text from images by recognizing patterns and shapes and turning them into editable text.
Answer: Absolutely! Once an image is converted to text, you can edit, copy, and paste it just like regular text, making it handy for various tasks.
Answer: OCR works well with clear fonts, but it might struggle with handwritten or complex fonts, affecting accuracy.