What exactly is OCR and OCR Datasets?
OCR (Optical Character Recognition) or short for short is a collection of technologies which work together to recognize text embedded within digital images. OCR can be utilized to read images in various formats, including pdf, JPG in addition to PNG. The objective is to find and locate pertinent text information within the images. For instance the PDF files appear to be filled with text, but they are simply pictures of printed pages. The software uses OCR technologies for this purpose "read" any text contained in the PDF file, and then output the text as a real text file, like Word-formatted documents.
In the workplace, OCR technology is often used to scan paper documents to digital format. The document created by the scanner is in fact an image-based file (typically the format PDF) regardless of whether you were scanning a text-based file. To convert the scanned document into a text document which can be easily searched and organized in the future, the words, letters and sentences of the original document need to be identified , and then extracted with OCR software.
What is the process behind OCR Datasets?
Optic character recognition is a process that involves six steps and several technologies. It is a process that works as follows:
Image Acquisition: A physical document is then scanned and converted to the form of a digital picture file. (This procedure is not required when the original document has been converted to digital.)
Preprocessing: Processing Of OCR Datasets to train OCR software to identify certain characters within image files.
Segmentation: The digital image is divided into smaller parts logically to make it easier to process. (Large images can require more time to be processed.)
Features extraction: Text characters within the image are detected and extracted, generally by detecting contrast between areas of light and dark.
Classification: Pattern recognition and feature detection methods are employed to determine particular characters.
Post-processing: Noise reduction, as well as other technologies are employed to cleanse and eliminate mistakes in the finished data.
After it, brand new text file is made. This file is then easily searched using particular keywords and phrases.
Improved Accuracy With OCR Training Dataset?
To get the most effective outcomes using OCR technology, it is essential to begin with a clear and clean document. An all-black photograph that is scanned at 300 dpi will yield the most precise character recognition. The problem arises when the characters on the document aren't sufficiently bold or blurred that could confuse OCR software. The characters should also not be too dark or contain "open" sections. This is unfortunately the case when faxing or copying documents.
Other issues may arise in the process of scanning. Scanning can introduce spots or noises into the resultant file, which could throw out OCR. OCR engine. Text that is distorted can cause problems, since OCR technology is best suited to pure horizontal text. It's also beneficial to use an uncomplicated font like Arial and Times New Roman; fancier fonts may confuse OCR technology. It is also possible to get greater results with the quality Dataset For Machine Learning scan device for documents. Find a scanner that is able to scan at least 25 pages per hour and has an auto sheet feeder to facilitate batch scanning.
Using OCR to aid in document Management?
Optic character recognition is an integral component in any management system. Simply scanning a paper document in digital format isn't very helpful, since all you have to do to create an image is save the file in the PDF format, JPG and similar formats. Since document management software and various other programs cannot read or comprehend text within images, it renders the document scanned more useful as the paper original document. This is the reason why OCR technology is essential. You can use OCR technology in order to read images that have been scanned and convert key information in organized digital data. This is crucial when handling legally binding contracts and purchase orders or any other important documents.
The procedure works as follows:
- The physical paper is then scanned.
- The image scanned is saved as the digital image file, usually in the PDF format.
- OCR software recognizes and removes the text from the scan and it saves it to an index digital storage.
- Document management software recognizes the key data within the digital document.
The digital data obtained by OCR technology is then protected, stored in a secure manner, indexable, and searched quickly and efficiently.
GTS works with efficiency of OCR Training Dataset
Global Technology Solutions (GTS) OCR solutions has got your business covered. With its remarkable accuracy of more than 90% and fast real-time results, GTS helps businesses automate their data extraction processes. In mere seconds, the banking industry, e-commerce, digital payment services, document verification, barcode scanning, Image Data Collection, AI Training Dataset, Video Dataset along with Data Annotation Services and many more can pull out the user information from any type of document by taking advantage of OCR technology. This reduces the overhead of manual data entry and time taking tasks of data collection.
