DocumentCode :
256360
Title :
Geometric model for vision-based door detection
Author :
Shalaby, M.M. ; Salem ; Khamis, A. ; Melgani, F.
Author_Institution :
Dept. of Mechatron., German Univ. in Cairo, Cairo, Egypt
fYear :
2014
fDate :
22-23 Dec. 2014
Firstpage :
41
Lastpage :
46
Abstract :
Emerging assistive technologies, such as assistive domotics and socially assistive robots have considerable potential for enhancing the lives of many elderly and physically challenged people throughout the world. Blind and visually impaired people can use these technologies for many tasks recognizing objects, handling various household duties, navigation in indoor and outdoor environments. Door detection is one of the important issues in indoor navigation. This paper presents a novel vision-based door detection technique. It is based on the geometric properties of the 4-side polygon. The efficacy of the proposed method is tested using large database of images with different levels of complexity. The experimental results show the robustness of the proposed method against changes in colors, sizes, shapes, orientations, and textures of the door. Detection rate of 83% with relatively low false positive rate for simple images is achieved. This proposed algorithm is suitable for real-time, portable applications where it only requires one digital camera and low computational resources.
Keywords :
assisted living; cameras; computational geometry; handicapped aids; image colour analysis; image texture; indoor navigation; object detection; object recognition; robot vision; service robots; visual databases; 4-side polygon; assistive domotics; assistive technologies; blind people; digital camera; door colors; door orientations; door shapes; door sizes; door textures; elderly people; geometric properties; household duties; indoor navigation; large image database; object recognition; physically challenged people; real-time portable applications; socially assistive robots; vision-based door detection technique; visually impaired people; Data preprocessing; Feature extraction; Image edge detection; Navigation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering & Systems (ICCES), 2014 9th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4799-6593-9
Type :
conf
DOI :
10.1109/ICCES.2014.7030925
Filename :
7030925
Link To Document :
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