Resizing

The Aspose.OCR recognition engine can handle images of any size. However, very small and very large image sizes can adversely affect recognition:

  • Small images may lose some detail due to noise removal, binarization, and automatic contrast correction.
  • Recognizing very large images can take much more time and resources.

Aspose.OCR offers flexible preprocessing filters that allow you to upscale small images, shrink large images, or resize an image to predefined width and height.

Proportional image scaling

To scale images up or down proportionally, use the OCR_IMG_PREPROCESS_SCALE preprocessing filter. The filter takes a scaling ratio (floating point number) as a parameter:

Scaling ratio Result Example
0 to 1 Shrink the image proportionally to the specified percentage. OCR_IMG_PREPROCESS_SCALE(0.3) - proportionally reduce the width and height of the image down to 30%.
1 Keep the original image size.
Above 1 Upscale the image proportionally to the specified percentage. OCR_IMG_PREPROCESS_SCALE(2) - proportionally increase the width and height of the image to twice its original size. 
std::string image_path = "source.png";
custom_preprocessing_filters filters_;
filters_.filter_1 = OCR_IMG_PREPROCESS_SCALE(0.8);
asposeocr_preprocess_page_and_save(image_path.c_str(), "result.png", filters_);

Manual image resizing

You can manually define the width and height of the target image (in pixels) using the OCR_IMG_PREPROCESS_RESIZE preprocessing filter.

std::string image_path = "source.png";
custom_preprocessing_filters filters_;
filters_.filter_1 = OCR_IMG_PREPROCESS_RESIZE(1500, 2500);
asposeocr_preprocess_page_and_save(image_path.c_str(), "result.png", filters_);

Usage scenarios

  • Medication guides.
  • Food labels.
  • Full-sized (raw) photos from high-resolution cameras and modern smartphones.
  • Scanned images at very high (300+) DPI.
Contrast correction Binarization