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<dependency>
<groupId>com.aspose</groupId>
<artifactId>aspose-ocr</artifactId>
<version>24.8.0</version>
</dependency>
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                                                  compile(group: 'com.aspose', name: 'aspose-ocr', version: '24.8.0')
                                                
                                              
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<dependency org="com.aspose" name="aspose-ocr" rev="24.8.0">
 <artifact name="aspose-ocr" ext="jar"/>
</dependency>
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libraryDependencies += "com.aspose" % "aspose-ocr" % "24.8.0"
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Java OCR Library

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Aspose.OCR for Java offers a developer-friendly API for optical character recognition that can work an any platform that supports Java. With just a few lines of code, you can integrate OCR features into your desktop solutions and services that can work an any device. Extract text from scans, photos, and screenshots, convert scanned pages into searchable, indexable PDFs, and perform text search and comparison on images.

Features and benefits

  • Global applications - supporting over 130 languages, the library allows you to recognize texts in Latin, Cyrillic and Asian scrips.
  • Read everything - retrieve text from any file obtained through a scanner or camera, and process images directly from web links.
  • Reliable results - achieve the highest recognition accuracy for all images, including those that are out-of-focus, rotated, distorted, and noisy.
  • Batch processing - bulk-recognize all images from folders and archives; read multi-page PDF documents, TIFF images and DjVu files.
  • Layout detection - identify and categorize content blocks in images to ensure the correct order of extracted text, regardless of layout.
  • Suitable for any content - image preprocessing and customizable document structure detection enable text extraction from virtually any image, ranging from high-quality scans to street photos.
  • Optimized - the library balances recognition speed, quality, and resource utilization for each specific use case.
  • Easy to use - you only need a few lines of code to convert image to text, create a searchable PDF, save recognition results to document, and many more.
  • Modular - keep your application lean and modular by selectively adding advanced features from our resource repository.

Supported file formats

  • .PDF - Portable Document Format
  • .JPG - JPEG, the most popular format for smartphone photos
  • .PNG - Portable Network Graphics, 24-bit with transparency
  • .TIFF - Tag Image File Format, commonly used for high quality scanning
  • .GIF - Graphics Interchange Format, limited to 256 colors
  • .BMP - Bitmap image file
  • .WBMP - Monochrome graphics file optimized for mobile devices

Multi-page PDF documents and TIFF images are fully supported.

Supported platforms

  • Microsoft Windows: Windows Desktop & Server (both x86 and x64)
  • macOS
  • Linux: Ubuntu, OpenSUSE, CentOS, and other Linux distributives

The system must support Java 2 Platform, Standard Edition (J2SE) 6.0 (1.6) or later.

Get Started

Aspose.OCR for Java API is hosted on the Maven repository or can be installed from the local package. For the detailed instructions, visit Installation article in online documentation.

Convert image to text

// Initialize Aspose.OCR recognition API
AsposeOCR api = new AsposeOCR();
RecognitionSettings recognitionSettings = new RecognitionSettings();
// Add image to the recognition batch
OcrInput source = new OcrInput(InputType.SingleImage);
source.add("image.png");
// Specify recognition language
RecognitionSettings recognitionSettings = new RecognitionSettings();
recognitionSettings.setLanguage(Language.ExtLatin);
// Extract text from image
ArrayList<RecognitionResult> results = api.Recognize(source, recognitionSettings);
System.out.println(result[0].recognition_text);

Read the Developer Reference for details on developing advanced applications with Aspose.OCR for Java.

Product Page | Docs | Demos | API Reference | Examples | Blog | Search | Free Support | Temporary License

VersionRelease Date
24.8.0September 2, 2024
24.6.0August 27, 2024
24.4.1July 17, 2024
24.6.1July 9, 2024
24.4.0April 13, 2024
24.3.0March 19, 2024
24.2.0February 19, 2024
24.1.0January 26, 2024
23.11.0November 30, 2023
23.10.0October 19, 2023
23.7.1July 31, 2023
23.7.0July 11, 2023
23.6.1June 27, 2023
23.6.0June 14, 2023
23.5.0May 22, 2023
23.4.0April 26, 2023
23.3.0March 29, 2023
23.2.0February 27, 2023
23.1.1January 27, 2023
23.1.0January 16, 2023
22.12.0December 15, 2022
22.11.1November 30, 2022
22.11November 21, 2022
22.10November 2, 2022
22.9September 28, 2022
22.8August 29, 2022
22.7July 25, 2022
22.6June 30, 2022
22.5May 23, 2022
22.4April 21, 2022
22.3March 31, 2022
22.2February 21, 2022
22.1February 2, 2022
21.12December 26, 2021
21.11November 19, 2021
21.10October 21, 2021
21.9September 22, 2021
21.8September 3, 2021
21.7July 30, 2021
21.1July 25, 2021
21.2July 25, 2021
21.3July 25, 2021
21.4July 25, 2021
21.5July 25, 2021
21.6July 25, 2021
20.9May 13, 2021
20.11November 29, 2020
20.10October 23, 2020
20.8August 31, 2020
20.7July 31, 2020
20.5May 26, 2020
17.11December 26, 2017
17.6July 26, 2017
17.3April 5, 2017
17.2March 6, 2017
17.01February 1, 2017
16.12December 30, 2016
16.11November 29, 2016
16.10October 22, 2016
3.7.0October 4, 2016
3.6.0August 29, 2016
3.4.0April 20, 2016
3.3.0March 9, 2016
3.2.0February 11, 2016