ATM Sign Language Recognition via Camera and Processor
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Solution Overview
Problem
Conventional ATMs are inaccessible to deaf individuals, particularly those with vision impairments, as they cannot fully interact with the machines, including remote teller assistants, due to the reliance on auditory and visual interfaces.
Innovation Solution
Incorporating a camera into the ATM to capture sign-language hand gestures, which are translated into input requests using a dictionary of sign-language patterns stored in memory, allowing deaf users to interact with all ATM features and using a unique hand gesture as a passcode for enhanced security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional ATMs use auditory and visual interfaces (keypad, screen, remote teller assistant), then the ATM provides convenient services to hearing and sighted users, but deaf individuals with vision impairments cannot fully interact with the ATM
Solution Approach 1:
The patent introduces sign language recognition technology as an intermediary between deaf users and the ATM system. The camera captures hand gestures, the processor translates them into commands, and the system executes corresponding operations, enabling deaf users to interact with the ATM without relying on traditional auditory or visual interfaces
Solution Approach 2:
The patent replaces the traditional mechanical keypad and visual screen interface with an optical-based sign language recognition system. Instead of requiring physical button presses or visual display interaction, the system uses camera capture and image processing to understand and execute user commands through hand gestures
2Reliability
If the ATM uses a traditional four-digit PIN code for authentication, then the authentication process is simple and fast, but the security is easily compromised as PIN codes can be guessed or discovered
Solution Approach 1:
The patent changes the authentication parameter from a numeric code (PIN) to a visual gesture-based identifier. Instead of requiring users to enter a four-digit number, the system captures and recognizes specific hand gestures as unique authentication identifiers, making the authentication process more secure while maintaining ease of use for deaf users
Data Source
AI summary
An automated teller machine includes a camera, a memory, and a hardware processor. The camera captures video data from a user, including at least one hand movement. The processor receives the video data from the camera and splits it into a sequence of images. The processor then splits each image into a set of features and forms vectors from the features. The processor uses the vectors to determine if each image belongs to a subset of images corresponding to a motionless sign-language pattern, or to a subset of images corresponding to a moving sign-language pattern. The processor stores the words and/or phrases assigned to each identified sign-language pattern in an input phrase. The processor determines that the input phrase represents a user request and then processes the request.