Enhancing Accessibility for Visually Impaired Users through a Hybrid Real-Time Multi-Object Recognition System
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Abstract
Visual impairment creates substantial challenges in performing object recognition tasks essential for independent living. Existing assistive vision systems typically rely on either classical computer vision techniques or deep learning models, limiting their robustness and practical applicability in real-world environments. To address these limitations, this study proposes a hybrid intelligent vision framework that integrates YOLOv8-based object detection for robust object localization, barcode recognition for reliable product verification, and ORB feature matching for fine-grained identification when barcode information is unavailable, thereby combining the complementary strengths of deep learning and classical computer vision. The dataset was designed to represent four common information-access tasks encountered by visually impaired individuals, including product labels, Thai banknotes, short shelf-life food products, and pharmaceutical items. An expanded dataset comprising 1,105 object classes and 7,927 images was constructed under diverse environmental conditions. The complete recognition pipeline was evaluated as an integrated mobile assistive system through both controlled and uncontrolled experiments to assess recognition accuracy, robustness, and the feasibility of practical deployment. Experimental results show that the proposed framework achieved 97.6% recognition accuracy, outperforming both the ORB–Barcode baseline (96.2%) and the standalone YOLOv8 model (97.0%), while maintaining near-real-time performance with an average processing time of 2.30 s per inference. User evaluation further demonstrated statistically significant improvements in task success rates among trained participants. The proposed framework improves recognition robustness while preserving computational efficiency on resource-constrained mobile devices, providing a practical, scalable, and user-validated assistive solution that enhances accessibility and supports independent living for visually impaired individuals.
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