New Metric for OCR Quality Evaluated

Researchers have developed a new way to measure the quality of Optical Character Recognition (OCR) technology, which is used to extract text from images. The current standard metric, called Character Error Rate (CER), has a flaw: it assumes that the text has been perfectly parsed, which is often not the case. To fix this, the researchers created a new metric called the Character Error Vector (CEV), which can be broken down into three parts: parsing errors, OCR errors, and interaction errors. This allows researchers to focus on the specific part of the process that's causing the most problems. The new metric was tested on a dataset of old newspaper images and found to be more accurate than traditional methods, even when the images are degraded and the text is hard to read.