Optical Character Recognition in USA

NidiTech Solutions - Image Recognition, OCR, and Handwritten Text Recognition Services can assist your company in leveraging AI to extract meaningful information from documents, handwritten notes, pictures, and video materials. It decreases human labour and makes day-to-day business activities considerably faster, better, and smarter.Our professionals will guide you through the process and ensure that the job is completed quickly and securely.

Optical Character Recognition software is referred to as OCR. Long before the advent of PDF or other digital document formats, the first iteration of OCR technology was invented in 1914. It was used to read and transform text strings into telegraph code. OCR is now used for everything from data input to licence plate recognition, and it's a critical tool for detecting and digitising handwritten and scanned documents without having to retype them

Optical Character Recognition (OCR) is a process by which Niditech is able to convert scanned images of text to electronic text so that digitized texts can be searched, indexed, and retrieved within the software. NiDitech OCR trainers will work with you in developing the language-specific OCR features that best fit your specific organizational needs. Training includes customizing the OCR process to ensure the highest level of accuracy and analysis to identify structural features, such as text orientation, headings, images, tables, captions, and paragraphs.

• OCR, ICR and Handwritten Text Recognition

• Image Tagging

• Face Detection

• Person Tracking

• Scene Understanding

• Object Identification

In a scan or rendering of a document, such as a legal document or a book scan, our Optical Character Recognition (OCR) technology will automatically detect printed text, handwriting, and numbers. It finds key-value combinations in document images automatically, allowing you to keep the document's natural context without the need for manual intervention. A group of linked data elements is referred to as a key-value pair.

• The lines and words of detected text

• The relationships between the lines and words of detected text

• The page that the detected text appears on

• The location of the lines and words of text on the document page

On a document, for example, the field "First Name" would be the key, while "JOHN" would be the value. This makes it simple to import the extracted data into a database or pass it to an application as a variable. Keys and values are recovered as basic text using typical OCR methods. Unless hard-coded rules are developed and maintained for each form, the relationship between them will be lost.