Common OCR Challenges and their Resolution

While Tesseract OCR utilizes Leptonica for some internal image preprocessing, additional steps are often necessary to achieve the best OCR accuracy. ImageMagick is a powerful tool that can be used for preprocessing images before running them through Tesseract OCR. It offers a wide range of capabilities such as resizing, deskewing, filtering, thresholding, and more, which can effectively prepare images for optimal OCR results. By leveraging ImageMagick preprocessing capabilities, you can enhance the quality of images and improve the accuracy of Tesseract OCR.

The specific image preprocessing techniques will largely depend on the unique circumstances of your project, the specific requirements you have, and the characteristics of the input images. To improve OCR quality, data analysts should experiment with various preprocessing techniques, OCR settings, and image enhancement methods. It may require iterative testing, fine-tuning, and adjusting parameters based on the specific challenges posed by the scanned documents. You can practice preprocessing your input documents on the OCR test environment (see…) and then provide the final optimal ImageMagick and Tesseract options in the JSON Settings section of the Document Set Details tab for document preprocessing and OCR.

Data analysts can face several challenges when preparing scanned document images for OCR and seeking ways to improve OCR quality. Here are some techniques that will help you tackle the most common OCR challenges: