Table of Content

Open Access iconOpen Access

ARTICLE

Line Trace Effective Comparison Algorithm Based on Wavelet Domain DTW

Nan Pan1, Yi Liu2, Dilin Pan2, Junbing Qian1, Gang Li3

1 Faculty of Civil Aviation and Aeronautical, Kunming University of Science & Technology, Kunming 650500, P.R. China
2 Kunming SNLab Tech Co., Ltd., Kunming 650228, P.R. China
3 Institute of Forensic science, Shijiazhuang Public Security Bureau, Shijiazhuang 050021, P.R. China

* Corresponding Author: Nan Pan, email

Intelligent Automation & Soft Computing 2019, 25(2), 359-366. https://doi.org/10.31209/2019.100000097

Abstract

It will face a lot of problems when using existing image-processing and 3D scanning methods to do the similarity analysis of the line traces, therefore, an effective comparison algorithm is put forward for the purpose of making effective trace analysis and infer the criminal tools. The proposed algorithm applies wavelet decomposition to the line trace 1-D detection signals to partially reduce background noises. After that, the sequence comparison strategy based on wavelet domain DTW is employed to do trace feature similarity matching. Finally, using linear regression machine learning algorithm based on gradient descent method to do constant iteration. The experiment results of line traces sample data comparison demonstrate the accuracy and reliability of the proposed algorithm.

Keywords


Cite This Article

APA Style
Pan, N., Liu, Y., Pan, D., Qian, J., Li, G. (2019). Line trace effective comparison algorithm based on wavelet domain DTW. Intelligent Automation & Soft Computing, 25(2), 359-366. https://doi.org/10.31209/2019.100000097
Vancouver Style
Pan N, Liu Y, Pan D, Qian J, Li G. Line trace effective comparison algorithm based on wavelet domain DTW. Intell Automat Soft Comput . 2019;25(2):359-366 https://doi.org/10.31209/2019.100000097
IEEE Style
N. Pan, Y. Liu, D. Pan, J. Qian, and G. Li "Line Trace Effective Comparison Algorithm Based on Wavelet Domain DTW," Intell. Automat. Soft Comput. , vol. 25, no. 2, pp. 359-366. 2019. https://doi.org/10.31209/2019.100000097



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1300

    View

  • 937

    Download

  • 0

    Like

Related articles

Share Link