Mercury Thermometer Scale Number OCR Recognition Dataset

In the current medical industry, temperature monitoring is a basic and important link. However, traditional mercury thermometers have issues with manual errors and untimely information transmission in data recording. Existing OCR solutions still have shortcomings in recognition accuracy and processing speed, such as poor adaptability to different lighting and angles. This dataset aims to solve the technical difficulties of real-time automatic recognition and improve the automation of medical data processing by providing a large amount of image data of mercury thermometer scale numbers. The dataset structure includes image ID, image data, and corresponding annotation information. Data collection is conducted using high-resolution professional cameras under standard lighting conditions to ensure image quality. In terms of quality control, multiple rounds of annotation and expert review are used to ensure data accuracy and consistency. Data is stored in JPEG format, organized by category and ID for classified management.