OCR Modalities Overview

Optical Character Recognition (OCR) technologies are designed to process and interpret text from various input images. Depending on the nature of the input, OCR can be classified into 3 categories.

Printed OCR

This modality is optimized for processing printed documents, typically consisting of structured text in black ink on a white background. These documents are often plain and well-formatted, such as reports, books, or official records. The printed OCR modality is highly efficient at recognizing standard fonts and layouts, making it ideal for digitizing traditional printed materials. Sample image as below.

Scenic OCR

Scenic OCR is designed to interpret text present in images that include natural or artificial scenes. These input images often combine visual elements such as landscapes, buildings, or objects with overlaid or embedded text. Scenic OCR is particularly useful for applications such as extracting text from signboards, advertisements, or product packaging, where the background and text are not standardized. Sample image as below.

Handwritten OCR

This modality focuses on recognizing text from scanned images of handwritten documents. These inputs typically include variable writing styles, uneven spacing, and inconsistent text alignment. Handwritten OCR is essential for digitizing historical documents, handwritten forms, or personal notes. Advanced techniques in this modality aim to accommodate the diverse characteristics of handwriting to ensure accurate recognition. Sample image as below.

Each modality addresses distinct challenges associated with input image types, enabling comprehensive OCR solutions for a wide range of use cases.