You are processing photos of runners in a race.
You need to read the numbers on the runners' shirts to identity the runners in the photos.
Which type of computer vision should you use?
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A. B. C. D.B
Optical character recognition (OCR) allows you to extract printed or handwritten text from images and documents.
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocrThe type of computer vision that should be used to read the numbers on the runners' shirts to identify the runners in the photos is optical character recognition (OCR).
OCR is a computer vision technique that allows machines to recognize and interpret printed or written characters from an image or a scanned document. In this case, OCR would allow the algorithm to recognize the numbers printed on the runners' shirts and convert them into a digital format that can be used for identification.
Facial recognition, on the other hand, would be used to identify individuals based on their facial features. This would not be useful in identifying runners based on their shirt numbers.
Semantic segmentation is a technique used to classify each pixel in an image into a specific category or class. This would not be useful in identifying the numbers on the runners' shirts.
Object detection is a technique used to identify and locate specific objects within an image. While it could be used to identify the runners in the photos, it would not necessarily be able to recognize the numbers on their shirts unless the algorithm had been specifically trained to do so.
Therefore, the best option for reading the numbers on the runners' shirts to identify the runners in the photos is optical character recognition (OCR).