|1/2018 - 2|
Real-time Multiresolution Crosswalk Detection with Walk Light Recognition for the BlindROMIC, K. , GALIC, I. , LEVENTIC, H. , NENADIC, K.
|Click to see author's profile on SCOPUS, IEEE Xplore, Web of Science|
|Download PDF (5,588 KB) | Citation | Downloads: 231 | Views: 324|
assistive technology, image recognition, machine vision, morphological operations, object detection
detection(9), image(8), traffic(5), processing(5), impaired(5), crosswalk(4), applications(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2018-02-28
Volume 18, Issue 1, Year 2018, On page(s): 11 - 20
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.01002
SCOPUS ID: 85043277157
Real-time image processing and object detection techniques have a great potential to be applied in digital assistive tools for the blind and visually impaired persons. In this paper, algorithm for crosswalk detection and walk light recognition is proposed with the main aim to help blind person when crossing the road. The proposed algorithm is optimized to work in real-time on portable devices using standard cameras. Images captured by camera are processed while person is moving and decision about detected crosswalk is provided as an output along with the information about walk light if one is present. Crosswalk detection method is based on multiresolution morphological image processing, while the walk light recognition is performed by proposed 6-stage algorithm. The main contributions of this paper are accurate crosswalk detection with small processing time due to multiresolution processing and the recognition of the walk lights covering only small amount of pixels in image. The experiment is conducted using images from video sequences captured in realistic situations on crossings. The results show 98.3% correct crosswalk detections and 89.5% correct walk lights recognition with average processing speed of about 16 frames per second.
|References|||||Cited By «-- Click to see who has cited this paper|
| L. Hakobyan, J. Lumsden, D. O'Sullivan, and H. Bartlett, "Mobile assistive technologies for the visually impaired," Surv. Ophthalmol., vol. 58, no. 6, pp. 513528, Nov. 2013. |
[CrossRef] [Web of Science Times Cited 27] [SCOPUS Times Cited 42]
 D. Dakopoulos and N. G. Bourbakis, "Wearable Obstacle Avoidance Electronic Travel Aids for Blind: A Survey," IEEE Trans. Syst. Man Cybern. Part C Appl. Rev., vol. 40, no. 1, pp. 2535, Jan. 2010.
[CrossRef] [Web of Science Times Cited 169] [SCOPUS Times Cited 246]
 R. Tapu, B. Mocanu, and E. Tapu, "A survey on wearable devices used to assist the visual impaired user navigation in outdoor environments," in Electronics and Telecommunications (ISETC), 2014 11th International Symposium on, 2014, pp. 14.
[CrossRef] [SCOPUS Times Cited 7]
 J. Choi, B. T. Ahn, and I. S. Kweon, "Crosswalk and traffic light detection via integral framework," in Frontiers of Computer Vision,(FCV), 2013 19th Korea-Japan Joint Workshop on, 2013, pp. 309312.
[CrossRef] [SCOPUS Times Cited 12]
 T. Asami and K. Ohnishi, "Crosswalk location, direction and pedestrian signal state extraction system for assisting the expedition of person with impaired vision," in Mecatronics (MECATRONICS), 2014 10th France-Japan/8th Europe-Asia Congress on, 2014, pp. 285290.
[CrossRef] [SCOPUS Times Cited 5]
 M. Radvanyi, B. Varga, and K. Karacs, "Advanced crosswalk detection for the Bionic Eyeglass," in 12th International Workshop on Cellular Nanoscale Networks and Their Applications (CNNA), 2010, pp. 15.
 M. S. Uddin and T. Shioyama, "Detection of Pedestrian Crossing Using Bipolarity Feature-an Image-based Technique," Trans Intell Transp. Sys, vol. 6, no. 4, pp. 439445, Dec. 2005.
[CrossRef] [Web of Science Times Cited 4] [SCOPUS Times Cited 14]
 J. M. Coughlan and H. Shen, "A fast algorithm for finding crosswalks using figure-ground segmentation," in Proc. 2nd Workshop on Applications of Computer Vision, in conjunction with ECCV, 2006.
 J. M. Coughlan and H. Shen, "Crosswatch: a System for Providing Guidance to Visually Impaired Travelers at Traffic Intersections," J. Assist. Technol., vol. 7, no. 2, Apr. 2013.
[CrossRef] [SCOPUS Times Cited 19]
 S. Wang, H. Pan, C. Zhang, and Y. Tian, "RGB-D image-based detection of stairs, pedestrian crosswalks and traffic signs," J. Vis. Commun. Image Represent., vol. 25, no. 2, pp. 263272, Feb. 2014.
[CrossRef] [Web of Science Times Cited 39] [SCOPUS Times Cited 48]
 M. Poggi, L. Nanni, and S. Mattoccia, "Crosswalk Recognition Through Point-Cloud Processing and Deep-Learning Suited to a Wearable Mobility Aid for the Visually Impaired," in New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops, 2015, pp. 282289.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]
 Y. Jie, C. Xiaomin, G. Pengfei, and X. Zhonglong, "A new traffic light detection and recognition algorithm for electronic travel aid," in Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on, 2013, pp. 644648.
[CrossRef] [SCOPUS Times Cited 18]
 V. Ivanchenko, J. Coughlan, and H. Shen, "Real-time walk light detection with a mobile phone," in Computers Helping People with Special Needs, Springer, 2010, pp. 229234.
[CrossRef] [SCOPUS Times Cited 15]
 S. Mascetti, D. Ahmetovic, A. Gerino, C. Bernareggi, M. Busso, and A. Rizzi, "Robust traffic lights detection on mobile devices for pedestrians with visual impairment," Comput. Vis. Image Underst., vol. 148, pp. 123135, Jul. 2016.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 12]
 K. Romic, I. Galic, and H. Leventic, "Influence of the input image resolution on the staircase detection," in ELMAR, 2016 International Symposium, 2016, pp. 177180.
[CrossRef] [SCOPUS Times Cited 1]
 W. Hackbusch, "Multi-Grid Methods and Applications", pp. 80-96, Springer Science & Business Media, 2013.
 C. Fernandez-Maloigne, F. Robert-Inacio, and L. Macaire, "Digital Color: Acquisition, Perception, Coding and Rendering", pp. 65-90, John Wiley & Sons, 2013.
 W. Burger and M. J. Burge, "Digital Image Processing: An Algorithmic Introduction Using Java", pp. 291-325, Springer, 2016.
 P. Soille, "Morphological Image Analysis: Principles and Applications", pp. 105-135, Springer Science & Business Media, 2013.
 K. Romic, I. Galic, and T. Galba, "Technology assisting the blindVideo processing based staircase detection," in ELMAR (ELMAR), 2015 57th International Symposium, 2015, pp. 221224
[CrossRef] [SCOPUS Times Cited 3]
Web of Science® Citations for all references: 256 TCR
SCOPUS® Citations for all references: 450 TCR
Web of Science® Average Citations per reference: 12 ACR
SCOPUS® Average Citations per reference: 20 ACR
TCR = Total Citations for References / ACR = Average Citations per Reference
We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more
Citations for references updated on 2018-06-22 12:46 in 111 seconds.
Note1: Web of Science® is a registered trademark of Clarivate Analytics.
Note2: SCOPUS® is a registered trademark of Elsevier B.V.
Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site.
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.