An Automatic Decoding Method for Morse Signal based on Clustering Algorithm

  • Yaqi Wang
  • Zhonghua Sun
  • Kebin JiaEmail author
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 63)


For technical problems of low accuracy of automatic decoding for Morse signal, an automatic decoding method for time-frequency spectrum of manual or mechanical Morse signal is put forward, which based on time-frequency analysis method and machine learning technology. It generates time-frequency image based on STFT, which used for extraction of Morse signal based on adaptive image enhancement later. K-means clustering algorithm have been introduced to identify the dots, dashes and interval between them. Error-correction algorithm put forward to improve the accuracy of decoding. Simulation experiment and engineering practice on Morse signal demonstrate the effectiveness and feasibility of this algorithm.


Morse Code Image Enhancement Automatic Decoding Clustering Algorithm 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Zahradnik P, Simak B. Implementation of Morse decoder on the TMS320C6748 DSP development kit[C]. European Embedded Design in Education and Research Conference. 2014,128-131.Google Scholar
  2. 2.
    Yang C H, Jin L C, Chuang L Y. Fuzzy support vector machines for adaptive Morse code recognition [J]. Medical Engineering & Physics, 2006, 28(9):925-31.Google Scholar
  3. 3.
    Qian S, Chen D. Joint time-frequency analysis[J]. IEEE Signal Processing Magazine, 1999, 16(2):52-67.Google Scholar
  4. 4.
    Cabal-Yepez E, Garcia-Ramirez A G, Romero-Troncoso R J, et al. Reconfigurable Monitoring System for Time-Frequency Analysis on Industrial Equipment Through STFT and DWT[J]. Industrial Informatics IEEE Transactions on, 2012, 9(2):760-771.Google Scholar
  5. 5.
    Gangwal O P, Funke E P, Varekamp C. Image enhancement: US, US 8331711 B2[P]. 2012.Google Scholar
  6. 6.
    Gonzalez R C, Woods R E. Digital Image Processing[J]. Prentice Hall International, 2002, 28(4):484 - 486.Google Scholar
  7. 7.
    Hartigan J A, Wong M A. A K-means clustering algorithm.[J]. Applied Statistics, 2013, 28(1):100-108.Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Beijing Laboratory of Advanced Information NetworksBeijingChina
  2. 2.College of Electronic Information and Control EngineeringBeijing University of TechnologyBeijingChina

Personalised recommendations