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Chinese Conference on Pattern Recognition

CCPR 2016: Pattern Recognition pp 105–118Cite as

Interactive Banknotes Recognition for the Visual Impaired With Wearable Assistive Devices

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 662))

Abstract

In this paper, we develop a new system, named WVIAS (Wearable Vision Impaired Assistive System), using camera-based computer vision technology to recognize banknote in natural scene aim to help visually impaired people. WVIAS is made up of two mainly parts. In the front, there is a micro camera, set on the glass or mounted on the helmet, to acquire video sequence. In the back, a high performance portable computer is planted to run processing algorithm. To make the system robust to variety conditions including occlusion, rotation, scaling, cluttered background, illumination change, viewpoint variation, and worn or wrinkled banknotes during recognition, we propose a method that using finger pointing as HCI to point out potential targeting district which we call region of interest (ROI), thereafter, we can sharply reduce the processing time by using ROI to replace original image combining with effective ORB feature. The HCI-based framework is effective in collecting more class-specific information and robust in dealing with partial occlusion and viewpoint changes. To authenticate the robustness and generalizability of the proposed approach, we have collected a large dataset of banknotes from natural scene. The proposed algorithm improved the mean average precision from 20.3 % to 61.6 %. The experiments result has shown the effectiveness of our proposal both on the natural scene static dataset and the dynamic video sequence.

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Notes

  1. 1.

    This is a general term for people with vision based disabilities, people who are blind have no vision while those with low vision have limited sight.

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Acknowledgement

The authors would like to thank all the reviewers for their insightful comments. This work was supported by the National Natural Science Foundation of China (Grant Nos. 61305033, 61273256 and 6157021026), Fundamental Research Funds for the Central Universities (ZYGX2014Z009).

Author information

Authors and Affiliations

  1. School of Automation Engineering, Center for Robotics, University of Electronic Science and Technology of China, Chengdu, China

    Dian Huang, Hong Cheng & Lu Yang

Authors
  1. Dian Huang
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  2. Hong Cheng
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  3. Lu Yang
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Corresponding author

Correspondence to Hong Cheng .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China

    Xuelong Li

  3. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Xilin Chen

  4. Tsinghua University , Beijing, China

    Jie Zhou

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  6. University of Electronic Science and Technology, Chengdu, Sichuan, China

    Hong Cheng

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© 2016 Springer Nature Singapore Pte Ltd.

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Huang, D., Cheng, H., Yang, L. (2016). Interactive Banknotes Recognition for the Visual Impaired With Wearable Assistive Devices. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-10-3002-4_9

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  • DOI: https://doi.org/10.1007/978-981-10-3002-4_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3001-7

  • Online ISBN: 978-981-10-3002-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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