The technique of translating photographs of typed, or printed text into machine-encoded text is known as optical character recognition (OCR).
OCR is commonly used to digitize printed documents, convert books and papers to electronic format, recognize text from images, and make text searchable and machine-readable. Optical character recognition has also many flaws.
The fact that quality is not always perfect, that it can be time-consuming and expensive, that it might produce erroneous results, that it is mistake-prone, and that it occasionally requires proofreading are all downsides of optical character recognition. Convert image to text
technology helps to find out the quality of your data perfectly.
In this article, we will discuss the drawbacks of OCR.
Quality is Not Always High:
The quality of OCR documents is one of the major drawbacks of optical character recognition. The quality of OCR is determined by the quality of the image provided as input. This means that OCR will have a harder time extracting text from an image if it contains any flaws. Moreover, you can identify this flaw more accurately convert image to text technology. OCR faults are more difficult to remedy since they frequently require the user to correct the OCR errors before re-processing with OCR.
OCR software cannot easily read handwritten documents. Similarly, non-Latin typefaces and typed fonts that mimic handwriting cause a lot of errors during the OCR process. It becomes hard for OCR to work well when documents are not of good quality or have weak contrast. Documents featuring both graphics and text provide a challenge for OCR. Spreadsheets will also result in additional mistakes. Convert image to text technology is one of the great tools that help you to seek out this drawback.
Lack of Information on Some Characters:
The lack of information on some characters, such as punctuation, is one of the issues with optical character recognition. Because they’re too little or non-contiguous, or because they’re upside down and backward, many punctuation marks are unreadable by OCR software.
Punctuation problems can also happen if the user uses the incorrect punctuation mark. Convert image to text is a feature which
is designed to correct the punctuation problem.
Inability to Recognize Some Languages:
If the text is in a language for which there is no OCR Language Pack, OCR may not be able to recognize it correctly. You can add OCR Language Packs to your OCR system as an optional component. Image to text assists to overcome the inability to recognize some languages. To improve the accuracy of the output, be sure that the OCR engine you’re using supports your language.
Optical character recognition has a number of drawbacks, one of which is its inaccuracy. This is due to the fact that OCR technology is not perfect and might make mistakes when translating photos to text. For instance, OCR
may misread a lowercase “l” as a “1” or a “b” as an “8.” If the text is utilized for crucial purposes, such as in a legal document, this can be dangerous. To ensure correctness, you may need to proofread the text after OCR. And image to text perfectly is the best choice there to point out the mistakes and correct them.
Inaccuracy with Damaged Texts:
OCR may not be able to recognize text that is printed in a style other than the language’s default font. It may also struggle to identify text that is set against a background that is darker than the text or has repeating patterns. These all mistakes can be checked with the help of image to text automation.
Although OCR is one of the most authentic software that provides a well-readable format for your images. But make sure that nothing is 100% perfect so that is the case with OCR. Using photo to text feature help to find out the mistakes and correct them properly.