Computer Vision Algorithm and Architecture Design for Visually-Impaired Aid System
Date Issued
2011
Date
2011
Author(s)
Lee, Chia-Hsiang
Abstract
Recently, vision technologies are gradually introduced to electronic aids to assist elder people or the visually-impaired. The most commonly used mobility tools - guide dogs and white canes, are inconvenient and expensive, and have limited usability in recognizing surrounding objects. Electronic vision-based visually impaired aids are smarter as navigation tools that can perceive rich visual information of the environment for the user. However,
state-of-the-arts are too bulky and still reveal many limitations such as detecting distant objects in outdoor environments In the thesis, we design a wearable vision-based visually impaired traffic analysis and navigation system for the visually impaired. The system aims to assist blind persons from basic needs to advanced requirements in their lives.
First, we develop an intelligent depth-based obstacle detection system that allows blind avoid from from the obstacles easily. Then, to understand the environment, we propose a depth characteristic analysis system to help
the blind get some information such as stair, road and wall. We also design a GPS-based visual navigation guide that combines recognition technology and the GPS function to provide higher accurate positioning result for the blind so that they can navigate independently even in an unfamiliar environment. Finally, we pick out the critical path in our system and design a new architecture to speed up the computational time. The chip is operated under 200MHz with 56mW in power consumption. Through our methodologies, 2000 frame with 640?80 resolution per second in general case and 28 frames per second in worst case. Totally speaking, we design a convenient portable vision-based visually impaired aid system for the visually impaired.
Subjects
Computer Vision
Visually-Impaired Aid System
Depth Map
Object Tracking
Depth Characteristic Mode
Segmentation
Vision-based Navigation System
Morphology
Pattern Recognition
Hardware Implementation
SDGs
Type
thesis
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