You must have been through many exams while in school and college. During those times, you are required to fill the test paper with pencils and mark them with black bullets. But, you’ve never known that there is a technology to process those papers and do the scoring. Now you know, it’s called Optical Mark Recognition (OMR).
What Is Optical Mark Recognition?
Optical Mark Recognition (OMR) is the process of collecting data from certain modules specified by the OMR and storing it in a computer. OMR collects information from people by recognizing characters on a document.
Optical Mark Recognition is performed with a hardware device (scanner) that detects the reflection or limited transmission of light on or through a sheet of paper. Optical Mark Recognition can process hundreds or thousands of documents per hour.
How does Optical Mark Recognition (OMR) Work?
The OMR uses a special scanner that focuses a beam of light on the affected area. Since black dots reflect less light than white areas, the scanner detects them.
Hence, digital paper design is prepared using several calculation algorithms. We are currently also using digital imaging techniques for Optical Mark Recognition. In this case, an image of the page is created, algorithms (mainly differential methods) are executed to extract the required contrasts.
Example of Use Case:
One of the most common use cases of Optical Mark Recognition technology is test evaluation. This technology has been helping the education sector very well for years. It helps education institutions to evaluate test papers very fast without doing any manual checking. This method has been used very widely around the world. Here’s an example of how OMR works:
What Is The Difference Between OMR and Optical Character Recognition (OCR)?
The difference between Optical Mark Recognition and OCR is that OMR is used to identify marks and bubbles on paper; mainly for examinations and surveys.
Read More About: Most Frequently Asked Questions about OCR
On the other hand, OCR is optical character recognition, which is used to recognize characters in documents, collect them and convert them into machine coding language for editing. Here are the comparison charts:
| Comparison | OMR | OCR |
|---|---|---|
| Definition | With the use of lines and shaded regions, a system that collects human marked data to detect the existence and placement of marked data such as markings. | A method of converting images of words in any kind of data into machine language in order to discern what it represents and store it in a systematic manner. |
| Feasibility | Easy | Mostly hard to implement |
| Use Cases | Customer feedback, surveys, voting, geo-coding, product evaluation, etc. | ID card extraction, invoice processing, logistics document extraction, etc. |
| AI Capability | No | Yes, on the enhanced generation |
It might seem like Optical Mark Recognition and OCR work the same and confuse anyone, but their goals are different. Technological progress is striking in a new way, but nothing can be perfect. Everything has different uses, pros, and cons.
By: Elsa Ajarwati
