What is OMR (Optical Mark Recognition) & How Does it Work?
OMR stands for Optical Mark Recognition. Its functioning is simple; it uses an optical scanner to detect marks on the paper. Then, it is pre-calibrated in a way that the backend software can quickly determine the data fed into the system. So, based on where and at what position the marks are made, helps OMR determine the fed data results. The concept and usage of OMR began with punch-hole systems. These systems would help the visually challenged. Now, it has developed from the feel of touch to the same detection system using hardware and software. What is a standout feature for OMR, is its accuracy. Based on how the marks are made and fed, its detection and result accuracy is superior to many other similar functioning technologies. Hence, it is widely used across industries and functions.What is OCR (Optical Character Recognition)?
Optical Character Recognition (OCR) is used to identify the characters from a physical document. It compares the identified marks with the preset character rules. The recognized figures are then compiled into an editable word document. OCR technology is extensively used for data entry purposes. We can see that a lot of apps are now available for smartphones that can perform similar functions. But, they are not perfect and serve more as a gimmick than actually performing for any enterprise. Also Read: Detailed Comparison of OCR and ICRHow are OCR and OMR Different?
OMR saw the light of the day as early as 1857 when it was used in a telegraph. IBM Corporation was the first company to create its scanner in the 1930s. Later in 1972, Scantron Corporation introduced widespread commercial use of OMR to the market. OCR was first founded in 1914 to help the blind read through the text. In 1974, Kurzweil Computer Products developed the Omni-font OCR machine. It could convert any handwritten or printed document into a digital format of any font. While OMR and OCR seem quite similar technologies, they widely vary in several ways. OMR recognizes whether there is any mark present in a predefined position. OCR, on the other hand, identifies the signs and characters and creates an editable word document of the scanned document. The primary purpose of OCR is to re-encode the already printed document without human intervention. The editable word document so created considerably resembles the original text. Even though not 100% accurate, it reduces manual efforts to a great extent. OMR is generally used in places such as evaluating the answer sheets of multiple-choice questions. Manually, a person would have to go through each answer and could get confused in the same. OMR is capable of scanning the entire document within no time. It reduces manual efforts and the probability of human error to a great extent. It is also used in lottery tickets. Implementation of OMR is a considerably simple affair as compared to OCR. In OCR, you design a system that analyzes the shape of the marks and then recognize the characters. Thus, implementing OCR needs more complex hardware as well as a software system. The document is first scanned into image format. The individual marks on the image are then mapped to a known character set.Conclusion:
Today, both OMR and OCR have their own set of markets and functions wherein they find applications. While OMR has found application majorly in the education industry, OCR is used across various industries. OCR is, therefore, witnessing more traction in comparison to OMR today. Though there are still many who doubt the accuracy of OCR, it has many times proven itself to be quite worthy of being the go-to technology.You May Also Like to Read: List of Best Open Source OCR Tools Available in the Market 10 Best OCR Apps for Mobile Phones (Android & iOS)
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