OCR technologies
You might be bored of manually entering data from images which is time-consuming and labor costing and you might be looking for an alternative to save time and cost. Today, we will go through the most Advance AI technology that can automatically recognize the text or characters on an image and convert them into machine readable files for further processing. In this article, we will discuss the OCR technologies, their usage, and understand their working principles step by step.
What is OCR?
OCR is the short form of Optical Character Recognition and is sometimes also known as text recognition. It is a process of identifying the text on an image and converting it to machine-readable text format. One of the main reasons for using OCR is that the computer converts the scanned files into image formatted files, which cannot be edited, counted words, or search for words using any text editor. So, in such cases, the OCR helps us to convert the images into text readable format.
By leveraging automated data extraction and storage capabilities, optical character recognition (OCR) technology is an effective business procedure that saves time, cost, and other resources by utilizing automated data extraction and storage capabilities. One more advantage is that OCR software can use artificial intelligence to create more advanced intelligent character recognition techniques, such as recognizing languages or handwriting styles as well.
Understanding the working of OCR
The working of OCR is very simple and easy to understand. Let us understand the working of OCR to convert an image formatted file to a machine-readable text file.
- Image acquisition: Mostly Optical character recognition uses the scanner to convert a hard copy of documents to an image. Usually, the converted image is a two-colored or black and white image. Then the dark spots on the image are treated as text or the characters that need to be recognized by the OCR and the white area is considered to be the background. The dart spots are then processed to find, or identify as alphabets, digits or special characters.
- Preprocessing: As we said, the dark areas on the images are processed to find the alphabets or digits. The preprocessing of the image file includes cleaning the image and removing errors or unnecessary spots to prepare the documents for reading and recognizing the text. The scanned document is cleaned either by using Deskewing process ( process to remove skew of an image by rotating in opposite direction) or by tilting the text to fix the aligning issues if there are any.
- Text recognition: After preprocessing the document, the next step is recognizing different patterns or characters using different techniques. OCR uses the two most commonly known algorithms for text recognition.
Pattern recognition algorithm: The OCR uses the pattern recognition method to compare and identify the patterns or characters in the preprocessed scanned document which has different fonts and formats. In other simple words, it compares the various fonts and formats of the text on the image to the ones that are already stored in it and recognize the characters.
Feature recognition algorithm: Feature recognition is simply finding and identifying the characters in the scanned file using some rules and predefined features. These rules and features can be the length of line, angle of the line, the crossing of the line, etc. For example, the word ‘L’ has two lines, horizontally and vertically which meet at the bottom at a 90 angle.
When the alphabet or character is identified, it is then converted into ASCII format for further processing by computer or machine.
- Final step: The last step of the OCR is to present you the scanned file in text readable format after recognizing the characters on it.
Types of OCR technologies
There are different types of OCR technologies based on their usage.
- Simple optical character recognition software
A simple optical character recognition works on a very simple principle by just comparing the font type and format to the ones which are stored in the database. It first stores different types of formats and font types in the database and when a scanned document is passed to recognize the text, it takes the dark spots and compares them with the stored fonts and if the system matches the text, then it converts the matched text to a machine-readable text file. This type of OCR is very limited as it cannot store all types of fonts and handwriting styles in the database so it may not be able to fully capture all the text on the preprocessed image. - Intelligent character recognition software
Most OCR systems nowadays use intelligent character recognition(ICR) technology as it is the most advance and accurate. This technology works in the same way as humans’ brains do. They are built by using strong machine learning and neural network predictive models. These ML and ANN models consider different attributes and characters of the text such as intersections, curves, and angles, and analyze the scanned image to give the final output. This technology processes each character on the scanned image one by one and gives the final results in seconds. - Intelligent word recognition
The intelligent word recognition technology is pretty much similar to the ICR as it is also based on ML and ANN predictive models that identify the characters on the image based on lines, curves, angles, etc. But the main difference is that, instead of processing each character on the scanned image one by one, the intelligent word recognition technology processes the whole image at once and outputs the text on the image as a machine-readable image. - Optical mark recognition
This is mostly used to find the text on a logo, watermarks in an image, or any other symbol that represents some characters that can be viewed in the text file.
Advantages and real-life applications of using OCR
The OCR has various advantages and applications. Different companies and organizations use OCR technologies for different purposes. Let us go through some of the common advantages and applications of OCR in real life.
- Read text from Photo: One of the biggest advantages of OCR technologies is that they can read the text from photos or images. For example the reading information on the ID card, passport, or, driver’s license.
- Searching text: Different companies and businesses can convert their hard copied text files into machine readable files using OCR technologies and which can be easily used to search different text and can be easily edited.
- OCR usage in banks Banking industries use the OCR technologies to convert loan documents, checks, transactions, and other financial documents into text format to store in their database. For example, the Thai Book Bank is used to read the information displayed on the Thai bank book page.
- OCR in healthcare industries: OCR is used in the healthcare sector to process patients’ records, including records of procedures, examinations, hospital stays, and insurance payments to convert the hard documents into machine readable files. OCR also assists in streamlining processes and reducing manual labor in hospitals while maintaining the accuracy of records.
- OCR and Artificial intelligence solutions: OCR is frequently incorporated into other artificial intelligence technologies that companies might use. For instance, it reads and scans licenses, number plates of vehicles, and traffic signs in self-driving cars, finds companies’ logos in social media posts, or recognizes packaging in advertisements and converts it into machine readable files for further processing.
- Reduction of manual entry mistakes using OCR: When people do repetitive tasks like manual data entry then the chances of occurrence of errors are high. OCR can automate these processes, minimizing human error and errors in manual data entry. The mistake rate can be even lower with AI and machine learning models in OCR.
Summary
Optical Character Recognition (OCR), also known as text recognition is a process of converting image formatted texts to a machine-readable text file. The process includes scanning the hard document, preprocessing the text on the image, and recognizing the text to make it a text readable file. The OCR technologies use various algorithms to detect and identify the text on the image. In this article, we discussed OCR, the working of OCR, and its applications in real life.
