Visionbridge: Enabling Independence Through Object, Face And Currency Recognition For The Blind

Abstract

Navigating Daily Life Can Be Especially Challenging For Blind And Visually Impaired Individuals, Particularly When It Comes To Identifying Obstacles, Recognizing Familiar Faces, And Handling Currency Transactions. Traditional Aids Such As White Canes And Guide Dogs, Though Helpful, Provide Limited Functionalities And Are Not Equipped To Handle Dynamic Environments Or Complex Tasks In Real Time. This Paper Introduces An Innovative Solution That Integrates Face Detection, Obstacle Detection, And Currency Recognition Into A Single, Wearable Device. By Utilizing Cutting-edge Artificial Intelligence, Including The Grassmann Model For Face Recognition, YOLO For Object Detection, And Convolutional Neural Networks (CNNs) For Currency Identification, The Proposed System Empowers Visually Impaired Individuals To Navigate Their Surroundings, Recognize People, And Manage Financial Transactions Independently. Real-time Image Capturing And Processing Allow For Immediate Audio Feedback, Ensuring Users Receive Context-sensitive Assistance As They Encounter Various Challenges In Everyday Settings. This System Not Only Enhances User Autonomy But Also Reduces Dependence On External Assistance, Fostering Greater Confidence And Independence. By Combining Multiple Functionalities In A Single, User-friendly Device, The Proposed Solution Addresses Gaps In Existing Technologies, Offering A Practical And Affordable Alternative For Enhancing The Quality Of Life Of Visually Impaired Individuals.

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