How do you evaluate OCR accuracy?

Measuring OCR accuracy is done by taking the output of an OCR run for an image and comparing it to the original version of the same text. You can then either count how many characters were detected correctly (character level accuracy), or count how many words were recognized correctly (word level accuracy).

How do I increase the accuracy of an OCR in Python?

13 Answers

1. fix DPI (if needed) 300 DPI is minimum.
2. fix text size (e.g. 12 pt should be ok)
3. try to fix text lines (deskew and dewarp text)
4. try to fix illumination of image (e.g. no dark part of image)
5. binarize and de-noise image.

What is accuracy of Tesseract OCR?

The method was evaluated using Tesseract and compared to ABBYY FineReader and HANWANG OCR. The following results are presented for Tesseract: the original set of samples achieves a precision of 0.907 and 0.901 recall rate, while the preprocessed set leads to a precision of 0.929 and a recall of 0.928.

What is OCR performance?

By isolating the document template’s entered text, an optical character recognition (OCR) engine can read and recognize much more accurately. In cases where filled data and and document images overlap, the dropout engine reconstructs the text as accurately as possible.

How can I improve my OCR results?

Increasing the accuracy of OCR can help achieve better results in terms of efficiency….5 Ways to Improve OCR Accuracy

1. Good Quality of Source Images. Before using OCR, make sure you can read the images with your own eyes.
2. Right Size of Images.
3. Remove Noise / Denoise.
4. Increase Image Contrast.
5. De-skew Original Source.

What is OCR model?

Optical character recognition (OCR) is the process of recognizing characters from images using computer vision and machine learning techniques. It uses a combination of text detection model and a text recognition model as an OCR pipeline to recognize text characters.

How do I optimize OCR?

5 Ways to Improve OCR Accuracy

1. Good Quality of Source Images. Before using OCR, make sure you can read the images with your own eyes.
2. Right Size of Images.
3. Remove Noise / Denoise.
4. Increase Image Contrast.
5. De-skew Original Source.