We just completed a mini-program project related to elderly care last week, which involved OCR (Optical Character Recognition) technology.

The application scenario is that after users have physical examinations or other checks in the hospital, they can directly use the mini-program to take photos. Through AI recognition technology, the text on physical examination reports and laboratory test sheets can be automatically recognized and then, according to classification, automatically stored in the corresponding fields of the mini-program. In this way, users don't need to input the information manually, and the loss of paper test documents can also be avoided.

In fact, this OCR text photo recognition technology can be applied in many other scenarios as well:

For example, for users' handwritten manuscripts, the content of the handwritten manuscripts can be directly and automatically recognized and recorded through OCR technology.

It can also automatically recognize the data in various types of tables, such as ruled tables, borderless tables, striped tables, handwritten tables and so on.

Another example is that it can automatically recognize the content in various minority languages, such as Latin, English, Thai, Korean, Russian and other languages.

It can also recognize the content of card and certificate information like ID cards, passports, birth certificates, and permits to enter Hong Kong and Macau. Then, combined with the ticket and certificate verification function, it can determine the authenticity of the documents. This solves the problem that in the early stage, many software had to rely on manual work to identify and judge the authenticity of the content uploaded by users. And the accuracy has also been greatly improved.

All of the above are common application scenarios for language and text recognition.

Later on, we will give a more detailed introduction to some application scenarios and technologies of OCR technology in other industries.

Alright, we are Yiyun Technology. Follow us. You need a reliable team.