Aspose.OCR  Cloud SDK for Java

Aspose.OCR Cloud SDK for Java

OCR Applications Development via Java REST API

Add Optical Character Recognition and Document Scanning functionalities to your Java applications in the cloud without any external dependencies.

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Aspose.OCR Cloud Java SDK helps software developers to include optical character recognition and documents scanning functionality inside their web and Windows applications with minimum efforts and cost. Java developers can easily add features like extracting text from images and files, character recognition in different languages, automated document layout detection, multi-platform support, and much more.

Aspose.OCR Cloud Java SDK makes it easy for Java developers to carry out OCR recognition operations on raster images (BMP, JPG, GIF, PNG, TIFF) in the cloud with just a couple of lines of Java code. Using the Java Cloud SDK the OCR operation can be performed either on a whole image or partial image. Recognizing text from a rectangular area as well as automatic & manual document layout detection is also fully supported.

Aspose.OCR Cloud Java SDK is now using an enhanced skew correction module and it is now possible to recognize slightly rotated images. It also provides an option to directly perform text recognition operation on image files available over web URL.

Advanced OCR API Features

Extract and recognize text from images via OCR

Recognize text from the whole or partial image

Specify portion of the image from which to extract text

Read character and font information from raster images

Return the response in XML or JSON format

Recognize English, French or Spanish text from the image

Recognize Slightly Rotated Images

Automated document layout detection

Recognize Text from URL Image

Get Started with Optical Character Recognition REST API

It is easy to get started with Aspose.OCR Cloud for Java and there is nothing to install. Simply create an account at Aspose for Cloud and get your application information. Once you have the App SID & key, you are ready to give a try to Aspose.OCR Cloud for Java.

Recognize & Extract Text from Images

Aspose.OCR Cloud Java SDK gives software developers the power to perform optical character recognition (OCR) on images to recognize and extract text from images so that it can be further processed or stored for later use. The API has provided classes and methods for scanning the whole image as well as scanning a specific area containing the characters. The Java cloud API supports recognizing and extracting information related to characters and fonts attributes.

OCR Text Recognition in Multiple Languages

Aspose.OCR Cloud Java SDK has provided support for detecting and recognizing characters of numerous languages inside cloud apps. At the moment it has provided support for recognizing text in English, French and German languages. It has also included support for a variety of fonts in different styles, like regular, bold, and italic, and different image formats.

Text Recognition from URL Image

Aspose.OCR Cloud Java SDK enables Java programmers to recognize text from URL images with just a couple of lines of code inside cloud-based applications. The SDK allows developers to directly perform text recognition operation on image files available over web URLs. It is not compulsory to upload it to any particular cloud storage. You just need to provide a correct URL of the available image.

Recognize Text of Different Languages

Aspose.OCR Cloud Java SDK enables software developers to perform an automatic skew correction to straighten images and recognize characters on the image. With advanced image skew, correction algorithm developers are now capable to recognize rotated images with ease and with just fewer lines of code. It can also successfully read poor quality scans and automatically make image pre-processing to correct low resolution, low contrast, noise and skew.

Supported image formats

*.bmp, *.dib *.jpeg, *.jpg, *.jpe *.jp2 *.png *.webp *.pbm, *.pgm, *.ppm *.pxm, *.pnm *.pfm *.sr, *.ras .tiff, *.tif *.exr *.hdr, *.pic

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