Abstract
In order to relieve the medical pressure, when patients with finger disability see a doctor, the degree of finger disability can be identified and judged by the equipment first, and then the doctor carries out the next step of diagnosis and treatment. Aiming at the problem that the traditional recognition algorithm is not ideal, this paper proposes a finger disability recognition algorithm based on Holistically-nested edge detection algorithm. On the basis of extracting the edge of hand image with Holistically-nested edge detection algorithm, the similarity judgment is made between the experimental object’s hand edge detection image and the standard hand edge detection image. The degree of finger joint integrity was analyzed by different similarity judgment, and then the degree of finger disability was judged. In order to verify the effectiveness of the method, 50 people’s hand images were collected to establish a sample database of hand images, and a total of 600 simulated severed finger images were tested. The accuracy of finger disability recognition was 96.6%. This algorithm can effectively identify the degree of finger disability and improve the medical efficiency.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chen, G., Xu, X.: General situation and development of production and supply of articles for the disabled in china. Chin. Rehabil. Theory Pract. 08, 63–65 (2002)
Wang, H., Tian, X., Mao, Y., Lu, X., Gu, Z., Cheng, L.: Application status, problems and suggestions of artificial intelligence in medical Field. Soft Sci. Health 32(05), 3–5+9 (2018)
Miller, R.P.: Finger dimension comparison identification system. US Patent, No. 3576538.1971
Ayurzana, O., Pumbuurei, B., Kim, H.: A study of hand-geometry recognition system. In: International Forum on Strategic Technology, pp. 132–135. IEEE (2013)
Xiong, W., Toh, K.A., Yau, W.Y., et al.: Model-guided deformable hand shape recognition without positioning aids. Pattern Recogn. 38(10), 1651–1664 (2005)
Morales, A., Ferrer, M.A., Díaz, F., et al.: Contact-free hand biometric system for real environments. In: 2008 16th European on Signal Processing Conference, pp. 1-5. IEEE (2008)
Gu, L., Zhenquan, Z., Zheng, G., Zaijian, W.: Hand shape matching algorithm based on feature fusion. Comput. Appl. 10, 2286–2288 (2005)
Li, Q.: Research on Hand Feature Recognition and Feature Level Fusion Algorithm. Beijing Jiaotong University (2006)
Yuan, W., Zhu, C., Li, K.: Analysis of correspondence between finger width selection and recognition rate. Opt. Precis. Eng. 17(07), 1730–1736 (2009)
Lanctao, J.: Research on Underhand Shape Recognition Method for Non-ideal Condition. Shenyang University of Technology (2014)
Kittler, J.: On the accuracy of the sobel edge detector. Image Vis. Comput. 1(1), 37–42 (1983)
Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(06), 679–698 (1986)
Xie, S., Tu, Z.: Holistically-nested edge detection. In: Proceedings of the 2015 IEEE International Conference on Computer Vision, pp. 1395–1403. IEEE, Piscataway (2015)
Funding
This research was funded by National Natural Science Foundation of China, grant number 62003222.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Bai, D., Zheng, X., Liu, T., Li, K., Yang, J. (2022). Finger Disability Recognition Based on Holistically-Nested Edge Detection. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13455. Springer, Cham. https://doi.org/10.1007/978-3-031-13844-7_15
Download citation
DOI: https://doi.org/10.1007/978-3-031-13844-7_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-13843-0
Online ISBN: 978-3-031-13844-7
eBook Packages: Computer ScienceComputer Science (R0)