Extracting handwritten text

To use this method, install handwriting recognition model in your project.

Aspose.OCR offers a special recognition algorithm for extracting handwritten text from images. It supports a number of European languages based on Extended Lain alphabet. Handwritten recognition has various business, government and personal applications:

Extract text from notes, memos and letters.
Convert historical records and documents into digital formats for archival purposes.
Parse resumes and employee records.
Analyze information from handwritten inventory lists to maintain accurate and up-to-date databases.
Analyze customer feedback and reviews to gain insights into customer preferences.
And many more.

To extract handwritten text from images, use recognize_handwritten_text() method of AsposeOcr class.

The method takes OcrInput object and returns OcrOutput object containing the text from images.

import aspose.ocr as ocr
# Initialize an instance of Aspose.OCR API
api = ocr.AsposeOcr()
# Add image to the recognition batch
input = ocr.OcrInput(ocr.InputType.SINGLE_IMAGE)
input.add("memo.jpg")
# Extract and show text
results = api.recognize_handwritten_text(input)
print(results[0].recognition_text)

Live demo

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Limitations

The method only supports a limited subset of Extended Latin letters and numbers.
Both uppercase and lowercase letters are recognized. However, the resulting text will be in uppercase.
This method does not support recognition settings. The recognition language is detected automatically.

Extracting text from receipts