光学字符识别（OCR）一般是指通过将文本区域的像素模式与熟悉的学习模式进行比较，在图像采集中自动识别字母数字字符，类似于一般的物体识别（如匹配）。
视觉功能 OCR 可根据适合不同应用的多种预训练字体（点阵字体、SEMI 字体、工业字体、手写体等）以及通过 "深度学习 "学习的通用字符字体来读取和解释文本。因此，无需额外培训就能达到很高的识别率。
此外，一行中的所有分段字符都会根据识别质量进行分级（GradingValue）。
有关 OCR 使用的寄存器概览，请参阅寄存器概览部分。
相关信息
有关视觉功能用例，请参阅OCR - 识别和读取字符。
有关视觉功能的常见问题，请参阅 OCRFAQ。
本节主题
Optical character recognition (OCR) generally refers to automated alphanumeric character recognition within image acquisitions by comparing the pixel patterns of the text areas with familiar learned patterns, analogous to general object recognition (such as in Matching).
Vision function OCR reads and interprets texts on the basis of several pre-trained fonts suitable for different applications (dot matrix fonts, SEMI fonts, industrial fonts, handwriting, etc.) as well as a universal font of characters learned via "deep learning". It is therefore possible to achieve very high recognition rates without additional training.
In addition, all segmented characters in a line are graded in terms of the quality of recognition (GradingValue).
For an overview of the registers used by OCR, see section Overview of registers.
Information:
For vision function use cases, see OCR - Recognizing and reading characters.
For FAQ about the vision function, see OCR FAQ.