Image Feature Analysis and Dynamic Measurement of Plantar Pressure Based on Fusion Feature Extraction

Ji Zou, Chao Zhang, Zhongjing Ma*, Lei Yu, Kaiwen Sun, Tengfei Liu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Footprint recognition and parameter measurement are widely used in fields like medicine, sports, and criminal investigation. Some results have been achieved in the analysis of plantar pressure image features based on image processing. But the common algorithms of image feature extraction often depend on computer processing power and massive datasets. Focusing on the auxiliary diagnosis and treatment of foot rehabilitation of foot laceration patients, this paper explores the image feature analysis and dynamic measurement of plantar pressure based on fusion feature extraction. Firstly, the authors detailed the idea of extracting image features with a fusion algorithm, which integrates wavelet transform and histogram of oriented gradients (HOG) descriptor. Next, the plantar parameters were calculated based on plantar pressure images, and the measurement steps of plantar parameters were given. Finally, the feature extraction effect of the proposed algorithm was verified, and the measured results on plantar parameters were obtained through experiments.

Original languageEnglish
Pages (from-to)1829-1835
Number of pages7
JournalTraitement du Signal
Volume38
Issue number6
DOIs
Publication statusPublished - Dec 2021

Keywords

  • Dynamic parameter measurement
  • Feature analysis
  • Fusion feature extraction
  • Plantar pressure

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