Perform OCR Online. Image to Text using Python SDK

Optical Character Recognition is a smart way to recognize content over raster images. It even becomes more useful when you need to preserve the old archival literature in a digital format. In this article, we are going to perform OCR online on various image formats. Please note that our Cloud SDK is capable of recognizing English, French, German, Italian, Portuguese and Spanish languages.
November 29, 2020 · 4 min · Nayyer Shahbaz

Perform OCR on Images. Optical Characters Recognition on Images using Java

Aspose.OCR Cloud enables you to perform Optical Characters Recognition and document scanning in the Cloud. It supports reading and recognition of text from most commonly used raster image formats (BMP, JPG, GIF, PNG, TIFF). Perform character recognition on images with fewer code lines. Simply pass a specific image to the Aspose.OCR Cloud API, and will return a response with recognized text. The API is capable of recognizing English, French, Spanish text and returns the response in XML or JSON formats.
June 24, 2020 · 3 min · Nayyer Shahbaz

Improved Text Recognition Module and Released Skew Correction Module in Aspose.OCR Cloud 18.6

[![][1] section of APIs Documentation. New Features and Enhancements Released skew correction module that allows to recognise slightly rotated images Integrated Tensorflow-Serving technology into our pipeline Improved text recognition module to fix a lot of issues in our roadmap: Fix issue of collapsing words Fix issue of duplicate letters Fix issues with punctuation symbols Learn to recognise characters: hyphen-minus (-), dash (–), grave accent (`), underscore (_), slashes (/)() Aspose Cloud Resources You may visit the following API resources for getting started and working with the API.
July 11, 2018 · 2 min · Mateen Sajjad

Introducing Version 3 of Aspose.OCR Cloud APIs

We are pleased to announce Version 3 of Aspose.OCR Cloud APIs. Aspose.OCR Cloud is a REST API for optical character recognition and documents scanning in the cloud. It supports reading and recognizing characters from most commonly used raster image formats. Just pass specific image name and its format to the Aspose.OCR Cloud REST API and it will return response in XML or JSON format including recognized text, font name, font size, font style.
December 27, 2017 · 2 min · Muhammad Sohail

New OCR algorithm support in Aspose.OCR Cloud 17.11

[![Aspose.OCR for Java logo][1] We are pleased to announce that Aspose.OCR Cloud 17.11 is now available for public use. This release supports new OCR based algorithm for image recognition. Enhancements Following enhancements have been introduced in this release. Support for new OCR algorithm. Advantages of this algorithm: It’s 5 times faster Excellent recognition results. Mean recognition quality is greater than 95% Supports more complex page layouts Supports rotated images Perfect stability of work Specification for functions to work with new algorithm Recognize image using Aspose.
November 8, 2017 · 1 min · Mateen Sajjad

New Release of Aspose.OCR Cloud SDK for Java – A Cloud SDK to Extract OCR or HOCR Text from Images in Java Using Powerful Aspose.OCR Cloud APIs

Aspose.OCR CloudAspose.OCR Cloud’s platform independent character recognition API is a true REST API that can be used with any language: .NET, Java, PHP, Ruby, Rails, Python, jQuery and many more. You can use it with any platform — web, desktop, mobile, and cloud. Aspose.OCR Cloud is a cloud-based REST API for optical character recognition and document scanning. It allows you to scan documents and recognize characters. Recognize text in English and other languages, and recognize text in only part of an image.
August 5, 2015 · 3 min · Farooq Sheikh

Extract Text from Images using Aspose Cloud .NET SDK

Aspose Cloud Aspose Cloud is a cloud-based document generation, conversion and automation platform for developers. Before Aspose Cloud, performing document processing and manipulation tasks in the cloud was not so easy. The Aspose Cloud APIs give developers full control over documents and file formats. Each API has been developed to offer you a wide range of features for file processing in the cloud. Aspose Cloud’s REST APIs are platform independent and can be used across any platform such as Node.
April 23, 2015 · 3 min · Zaheer Tariq

Unit Tests for Aspose.OCR API Added to Aspose Cloud Android SDK

Aspose.OCR Cloud is a cloud-based REST API for optical character recognition and document scanning. It allows you to scan documents and recognize characters. Recognize text in English and other languages, and recognize text in only part of an image. Aspose.OCR Cloud supports a variety of fonts in different styles, like regular, bold, and italic, and different image formats. You can use Aspose.OCR Cloud in many scenarios, for example, extracting text and saving to a database.
November 6, 2014 · 2 min · Muhammad Sohail

Aspose.OCR Cloud REST API Documentation Changes Introduced During The Month Of February 2013

Aspose.OCR Cloud is a REST API that allows text extraction and character recognition from images in the cloud. Aspose.OCR Cloud supports optical character recognition for images in different formats such as TIFF, BMP, JPEG etc. You can utilize Aspose.OCR Cloud SDK examples to extract image text from images and PDF files for different languages like .NET, Java, PHP and Python. During the month of February 2013, we have added some features that you can use to extract text and recognize the characters.
February 26, 2013 · 1 min · Fatima Rabbiya

Extract text from images using Aspose.OCR Cloud REST examples in PHP

Aspose.OCR Cloud is a REST API for optical character recognition and document scanning.Aspose.OCR Cloud API also supports character recognition for multiple languages such as English, French and Spanish. The accuracy, high speed and ease of use make Aspose.OCR Cloud the perfect choice for text extraction from images in cloud. Previously, we have provided SDK and REST examples for text extraction from images in different programming languages such as .NET, RUBY and Java.
February 19, 2013 · 3 min · Fatima Rabbiya