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An Obstacle Detection Method for Visually Impaired Persons by Ground Plane Removal Using Speeded-Up Robust Features and Gray Level Co-Occurrence Matrix

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Abstract

Rapid boost in the density of the pedestrians and vehicles on the roads have made the life of visually impaired people very difficult. In this direction, we present the design of a smart phone based cost-effective system to guide visually impaired people to walk safely on the roads by detecting obstacles in real-time scenarios. Monocular vision based method is used to capture the video and then frames are extracted out of it after removing the blurriness caused by the motion of camera. For each frame, a computationally simple approach based on the ground plane is proposed for detecting and removing the ground plane. After removing ground plane, features like Speeded-Up Robust Features (SURF) of the non-ground area are computed and compared with features of obstacles. An active contour model is used to segment the area of non-ground image whose SURF features are matched with obstacle features. This area is referred as Region of Interest (ROI). To check whether ROI belongs to an obstacle or not, Gray Level Co-occurrence matrix (GLCM) features are calculated and passed onto a classification model. Classification results show that this system is efficiently able to detect the obstacles that are known to the system in near real-time.

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Authors and Affiliations

  1. Computer Science and Engineering Department, University Institute of Engineering and Technology, Panjab University, Chandigarh, 160014, India

    A. Jindal, N. Aggarwal & S. Gupta

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  1. A. Jindal
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  2. N. Aggarwal
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  3. S. Gupta
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Correspondence to A. Jindal.

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Anish Jindal received the B. Tech. degree from Punjab Technical University in 2012 and M.E. degree from University Institute of Engineering and Technology, Panjab University in 2014, both in Computer Science Engineering. He has successfully qualified GATE, NET and JRF examinations held by IIT, UGC and CSIR respectively. His research interests include image processing, ad-hoc networking and data analytics. He is also the member of IEEE and ACM.

Naveen Aggarwal is actively working in the area of Computer Vision and Data Mining. He did his PhD from GGSIPU, Delhi in year 2011 and M. Tech. in Computer Science and Engineering from IIT, Kharagpur. Dr. Aggarwal has been awarded with Faculty Innovation award from the Infosys foundations. Different Effort Estimation Model developed by Dr. Aggarwal are appreciated and being used by Axede Corporation, USA and Birlasoft Corp. India. He has over 18 publications in International journals and 55 publications in international and national conferences. He has joined PU as Asstt. professor in Computer Science and Engineering at UIET in February 2005. Earlier, he has worked for three years from 2002 to 2005 in Punjab Engineering College, Chandigarh.

Savita Gupta received the B. Tech. degree from TITS, Bhiwani (Haryana), in 1992, M.E. degree from TIET, Patiala, Punjab, in 1998 both in computer science and engineering. She obtained her PhD degree from PTU, Jalandhar in 2007 in the field of ultrasound image processing. She has been in the teaching profession since 1992. Presently, she is working as professor in the Department of CSE, University Institute of Engineering and Technology, Panjab University, Chandigarh. Her research interests include image processing, image compression and denoising, and wavelet applications.

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Jindal, A., Aggarwal, N. & Gupta, S. An Obstacle Detection Method for Visually Impaired Persons by Ground Plane Removal Using Speeded-Up Robust Features and Gray Level Co-Occurrence Matrix. Pattern Recognit. Image Anal. 28, 288–300 (2018). https://doi.org/10.1134/S1054661818020086

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  • DOI: https://doi.org/10.1134/S1054661818020086

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