szövegfelismerést

Szövegfelismerés, often translated as text recognition or optical character recognition (OCR), is the process of converting images of typed, handwritten, or printed text into machine-encoded text. This technology is crucial for making scanned documents and images of text searchable, editable, and accessible for digital processing.

The fundamental principle behind most text recognition systems involves several key stages. First, image preprocessing is performed to enhance the quality of the input image. This can include steps like deskewing (correcting rotation), noise reduction, and binarization (converting the image to black and white). Following preprocessing, the system identifies individual characters or words within the image. This segmentation is often challenging, especially with complex layouts or handwritten text.

Once segmented, the actual recognition phase takes place. This typically employs pattern matching techniques, where the shapes of the characters in the image are compared against a database of known character forms. More advanced systems utilize machine learning models, particularly deep learning, which can learn to recognize characters and even understand context with high accuracy, even for variations in fonts, sizes, and handwriting styles.

The output of text recognition is usually plain text, which can then be used for various applications. These include digitizing historical archives, creating searchable PDFs, enabling translation software, and powering assistive technologies for visually impaired individuals. The accuracy of text recognition systems has significantly improved over the years, making them an indispensable tool in many fields.