Content areas detection

A scanned image or photograph of a text document may contain a large number of blocks of various content - text paragraphs, tables, illustrations, formulas, and the like. Detecting, ordering, and classifying areas of interest on a page is the cornerstone of successful and accurate OCR. This process is called content areas detection.

Aspose.OCR offers several content areas detection algorithms, allowing you to choose the one that works best for your specific content.

Area detection modes

You can manually override the default content areas detection method if you are unhappy with the results or get unwanted artifacts.

Document structure analysis algorithm is specified in an optional DetectAreasMode parameter of recognition settings.

# Instantiate Aspose.OCR API
api = AsposeOcr()
# Add image to the recognition batch
input = OcrInput(InputType.SINGLE_IMAGE)
input.add("source.png")
# Set document areas detection mode
recognitionSettings = RecognitionSettings()
recognitionSettings.detect_areas_mode = DetectAreasMode.MULTICOLUMN
# Recognize the image
result = api.recognize(input, recognitionSettings)
# Print recognition result
print(result[0].recognition_text)
input("Press Enter to continue...")

Aspose.OCR for Python via .NET supports the following document structure analysis methods provided in DetectAreasMode enumeration:

Name	Description	Use cases
DetectAreasMode.UNIVERSAL	Detects all blocks of text in the image, including sparse and irregular text on street photos. Used by default. See DetectAreasMode.UNIVERSAL for additional details.	Photos Screenshots Advertisements Datasheets Street photos Price tags Food labels
DetectAreasMode.MULTICOLUMN	Detects large blocks of text formatted in several columns. See DetectAreasMode.MULTICOLUMN for additional details.	Contracts Books Articles Newspapers
DetectAreasMode.LEAN	Do not analyze document structure. Prioritizes speed and reduces resource consumption by omitting support for complex layouts.	Simple images containing a few lines of text without illustrations or formatting. Applications requiring maximum recognition speed Web applications
DetectAreasMode.TABLE	Detects cells in tabular structures. See DetectAreasMode.TABLE for additional details.	Tables Invoices
DetectAreasMode.CURVED_TEXT	Auto-straightens curved lines and finds text blocks inside the resulting image. See DetectAreasMode.CURVED_TEXT for additional details.	Photos of books, magazine articles, and other curved pages.