When processing photos of runners, which type of computer vision would be ideal for reading their shirt numbers?

Optical character recognition (OCR) is the ideal technology for reading shirt numbers on photos of runners because it is specifically designed to convert different types of documents, including images of text, into machine-readable text. OCR involves analyzing the shapes of the letters and numbers in an image and translating them into text that can be processed by computers. This is particularly relevant for shirt numbers, which are typically clear and numeric or alphanumeric characters that OCR systems are adept at recognizing.

In contrast, facial recognition is focused on identifying and verifying human faces, making it unsuitable for reading shirt numbers. Object detection involves identifying and locating objects within an image but does not directly interpret text. It would tell you that there is a person wearing a shirt, but it wouldn’t extract the numbers. Image classification categorizes the entire image into predefined classes without detailing specific elements within it, such as text. Therefore, OCR stands out as the necessary technology for accurately reading the shirt numbers from the images of runners.