Extraction of OCR Datasets And It's Use Cases

Introduction

OCR (Optical Character Recognition) is a technology that enables machines to read and recognize printed or handwritten text from images or documents. The process involves converting an image or scanned document into a digital format that can be edited and searched. OCR technology has been widely used in various industries, including finance, healthcare, and education, to automate data entry, improve accuracy, and increase efficiency. To train an OCR system, large datasets of labeled images with accurate text transcription are required. The extraction of OCR datasets involves collecting and processing large volumes of data, such as scanned documents, images, and text files, and then manually transcribing the text content in the images to create labeled datasets. This process can be time-consuming and expensive, but it is essential for developing accurate OCR models.

What is OCR data extraction

OCR (Optical Character Recognition) data extraction is a process of automatically extracting text information from scanned or digital images using OCR technology. OCR technology analyzes the image of a document and identifies the characters in it, then converts the characters into digital text that can be searched, edited, and analyzed by a computer.

OCR data extraction is particularly useful for organizations that have a large volume of documents in paper or image format that they need to convert into searchable digital format. For example, extracting OCR Datasets can be used to extract information from invoices, receipts, forms, and other types of documents. Once the text is extracted, it can be used for a variety of purposes, such as data entry, data analysis, and document management. Overall, OCR data extraction can significantly reduce the time and effort required to process large volumes of paper or image documents, making it a valuable tool for businesses and organizations that deal with large amounts of information.

Types of OCR Datasets

OCR, or Optical Character Recognition, is the process of converting scanned or photographed images of text into editable, searchable text. There are several types of OCR, including:

Handwritten OCR: This type of OCR recognizes handwritten text and converts it into editable text.

Printed OCR: Printed OCR is the most common type of OCR and is used to recognize printed text from scanned documents.

Intelligent OCR: Intelligent OCR uses artificial intelligence algorithms to recognize and classify different types of text, including handwritten and printed text, and can also identify specific types of information, such as names, dates, and addresses.

Zonal OCR: Zonal OCR is used to recognize specific zones or sections of a document, such as the header or footer, and extract information from those zones.

Mobile OCR: Mobile OCR is used on smartphones and tablets to capture and recognize text from images taken with the device's camera.

Cloud OCR: Cloud OCR is a web-based OCR service that allows users to upload images or documents and receive the recognized text as output.

Applications of OCR

OCR (Optical Character Recognition) technology is widely used in various applications. Here are some of the applications of OCR:

Digitization of Printed Material: OCR is used to convert printed material into digital text that can be edited, stored, and shared easily.

Document Management: OCR is used in document management systems to automatically extract text from scanned documents and make it searchable.

Data Entry: OCR is used to automate data entry tasks by extracting text from paper documents and entering it into databases or other digital systems.

Image-to-Text Conversion: OCR can convert text from images, such as scanned documents, photographs, and screenshots.

Text-to-Speech: OCR technology can be used to convert text to speech for visually impaired users.

Translation: OCR technology can be used to translate text from one language to another.

Handwriting Recognition: OCR can be used to recognize and convert handwritten text into digital text.

How Extraction of OCR Datasets And It's Use Cases used for GTS.AI

Globose technology Solutions (GTS.AI) is a company that specializes in providing OCR Datasets and related Video Annotation and Traffic Video Dataset services to businesses and developers. Their datasets include a variety of image types, such as handwritten documents, printed text, and business cards. GTS.ai also provides annotation services, which involves labeling images with their corresponding text content, and data processing services, which involve automating data entry and document processing tasks.

Comments

Post a Comment

Popular posts from this blog

Image
Following The Right Structure For Text Data Mining  Glance Everyday we interact with various media (such as audio, text images, videos, and text) depending on our brains to process what we see and draw sense of it to guide our actions. The most commonly used kinds that media are text which is the basis of the languages that we use to communicate. Since it is so widely used, annotation of text needs to be performed with precision and completeness. Machine learning (ML) the machines learn to read, comprehend and process, as well as produce text in a useful way to interact with humans via technology. As per the 2020 State of AI and Machine Learning report 70% of businesses said that text is a kind of data they employ in the AI solutions. It is not surprising, considering that the revenue-generating and cost-saving benefits of using text-based AI across all sectors are immense. As computers advance in their ability to read human speech, the value of training with high-quality text data is
Read more

The Real Hype Of AI In Retail Market And Ecommerce

Image
  Artificial Intelligence in Retail Market hype was all the rage in the past year, and the truth of A.I.   is hot today.   Actually the majority of companies declare that they have made use of A.I.   throughout their business in 2017, an increase of 31 percent over 2016.   and 791 publicly-traded companies included A.I.   during their earnings calls during Q3 2017. What is this referring to?   It is a sign that A.I.   is on the verge of reaching "big data" or "blockchain" the level of fame.   In the near future, even the most unlikely of companies will claim to be using the technique (imagine Long Island Iced Tea becoming an blockchain company) to keep up with the current trend and earn some positive publicity.   In reality, TGI Fridays is using A.I.   to make cocktails automatically tailored to your preferences. Alexa will transform into a mixologist from the convenience of your own home.   This is a great way to make use of A.I.   and an amazing customer experien
Read more
Image
GTS.AI smoothers VIDEO DATASET mining for AI projects. Glance Video Mining is identifying patterns in audiovisual content without supervision. The job mining process can take advantage of its temporal (motion) and spatial (color textures, forms, and text section) characteristics. The process of obtaining useful information from massive data sets demands the application of visual methods for data mining that visualize knowledge and data. Visual data mining combines these two elements, making it an attractive and effective way to understand the distribution of data patterns, clusters, and outliers. The GTS has discovered that data video and data mining can be two different fields that can join to produce visually-based data mining. It could also be linked to multimedia systems, high-performance computing, pattern recognition, computer-human-computer interaction, and graphics. It can typically combine data mining and data video in different ways. Data videos in the context of GTS, the dat
Read more