App1 requires the extraction of text (brand names) from visual data (images/photos). Optical character recognition (OCR) is the precise AI technique designed for recognizing and extracting text from images, making it the most accurate choice over the broader Image Analysis. App2 describes a system for touchless access control, which universally relies on biometric identification, specifically Face recognition and verification, for authentication to grant entry. The Azure AI Vision Face service provides the necessary capabilities for identifying individuals to enable this functionality.

Microsoft Official Documentation (Azure AI Services - Vision):

Topic: Azure AI Vision Overview and Capabilities (OCR).

Reference: Official vendor documentation on the Read API or OCR, detailing its ability to "extract text from images and documents," which includes text like brand names. (Specific section on Optical Character Recognition).

IEEE Xplore Digital Library:

Topic: Face Recognition in Access Control Systems.

Reference: An academic paper discussing the application of face recognition algorithms (specifically detection, verification, and identification) for secure access systems. (e.g., IEEE Access, Section on Biometric Systems).

MIT OpenCourseWare (Courseware on Computer Vision):

Topic: Fundamentals of Optical Character Recognition.

Reference: Course materials defining OCR as the method for converting "scanned images of text into machine-encoded text," directly applicable to extracting text like brand names from photos. (e.g., Lecture notes on Document Analysis).

Cambridge University Press (Academic Publication on Biometrics):

Topic: Biometric Authentication for Physical Access.

Reference: Textbook chapter explaining that face recognition is a common, non-contact biometric method used for access control and security applications. (e.g., Chapter on Non-Contact Biometrics, pages 70-75).