Work

Low-Cost Smart Cane for Visually Impaired People with Pathway Surface Detection and Distance Estimation Using Weighted Bounding Boxes and Depth Mapping

Year: 2025

Type: article

Abstract: Visually impaired individuals are at a high risk of accidents due to sudden changes in walking surfaces and surrounding obstacles. Existing smart cane systems lack the capability to detect pathway surface transition points with accurate distance estimation and danger-level assessment. This study proposes a low-cost smart cane that integrates a novel Pathway Surface Transition Point Detection (PSTPD) method with enhanced obstacle detection. The system employs dual RGB cameras, an ultrasonic sensor, and YOLO-based models to deliver real-time alerts based on object type, surface class, distance, and severity. It comprises three modules: (1) obstacle detection and classification into mild, moderate, or severe levels; (2) pathway surface detection across eight surface types with distance estimation using weighted bounding boxes and depth mapping; and (3) auditory notifications. Experimental results show a mean Average Precision (mAP@50) of 0.70 for obstacle detection and 0.92 for surface classification. The average distance estimation error was 0.3 cm for obstacles and 4.22 cm for pathway surface transition points. Additionally, the PSTPD method also demonstrated efficient processing with an average runtime of 0.6 s per instance.

Source: Information

DOI: 10.3390/info16080707

Authors: Teepakorn Mungdee, Prakaidaw Ramsiri, Kanyarak Khabuankla, Pipat Khambun, Thanakrit Nupim, Ponlawat Chophuk

Institution: Burapha University

Language: English

Topic: Assistive Technology in Communication and Mobility

Subfield: Occupational Therapy

Field: Health Professions

Domain: Health Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $1,930