Optical character recognition (OCR) is the process of converting printed or handwritten text into text that can be processed by computers by scanning. This technology allows documents to be digitized quickly, so that the data can be searched, edited and shared more easily. The OCR software separates the letters in the image, converts them into words and creates sentences from the words. In other words, it allows the transfer of original content derived from physical media to digital media. It also supports you to access and edit many contents digitally. Besides, OCR is a system that eliminates the need to enter data manually. Especially in recent years, many innovative software has been developed for handwriting OCR for modern businesses. These software provide comfort and time saving for businesses.
Handwriting OCR problems and Solutions
Although OCR technology provides significant benefits for your business, it also has its challenges. Underneath are a few common challenges that businesses may confront when utilizing OCR in RPA workflows and a few techniques to overcome them:
- Language and font recognition: OCR technology may have difficulty recognizing fonts and certain languages, especially rare or not supported by OCR software. To overcome this challenge, it is important to use an OCR software that supports the fonts and languages you need, and to make sure that the OCR engine is trained to recognize them correctly.
- Poor image quality: OCR performance may be affected by the quality of the scanned image or document. Insufficient lighting, low resolution, or curved documents may affect the accuracy of OCR. To overcome this challenge, it is vital to guarantee that the pictures are of tall quality and well-positioned some time recently they are handled with OCR. Text recognition errors: OCR technology is not error-free, and errors may occur during the text recognition process.
Handwriting OCR Pros
The advantages of handwriting OCR for digital businesses include accessibility, time savings, storage efficiency and accuracy. For example, the transfer of physical documents to digital media ensures that these documents are accessible anytime and anywhere. In addition, storing documents in digital formats helps to save time, as they are searchable and editable. In terms of accuracy, OCR technology allows even handwritten or poorly written notes to be accurately digitized.
If we summarize OCR technology, we can say that it is an important tool that saves time and energy and plays a critical role in the transfer of texts to digital media, especially for digital enterprises.
OCR Algorithms
There are two types of OCR algorithms. The first of these algorithms is matrix matching. Matrix matching involves comparing an image on a pixel-by-pixel basis with a glyph stored in the program. This method is based on the presence of the character being recognized in the image in a similar font and in the same scale glyph. Matrix matching works best on typewritten texts and loses its efficiency when faced with new fonts. This is the technique that photocell-based OCR uses.
The second algorithm is feature extraction. Feature extraction breaks down glyphs into features such as lines, curves, line direction, and line intersections. This subtraction process reduces the dimensionality of the representation and makes the recognition process efficient. These properties are compared to an unique vector-like representation of a character that can be diminished to one or more glyph models. This technique is used in many modern OCR programs and handwriting recognition.
Areas where OCR Is Used?
OCR is used to speed up operations in many areas of our lives. In addition to making it possible for this technology to do things that cannot be done by humans, such as automatic license plate recognition, it also allows written documents to be transferred to digital media at speeds that people will never reach. Other areas where this technology is used; data entry for business documents such as checks, passports, invoices and receipts, passport recognition at airports, traffic sign recognition, business card information removal to the contact list, faster digitization of written documents, simultaneous transfer of handwriting to a digital medium and support applications for visually impaired users can be divided into. The OCR algorithm and program used will change according to the field of interest.
