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Classification and recognition method of intelligent storage goods based on visual servo

Author

Listed:
  • Jinbin Zhao
  • Liyu Ma
  • Fei Gao
  • Shujian Chen

Abstract

This paper proposes an intelligent storage goods classification and recognition method based on visual servo. The camera coordinates are calibrated based on the visual servo system, and the quaternion Gabor filter convolution algorithm is used to extract the characteristic area of intelligent storage goods. The case differentiation algorithm is used to realise the characteristic area classification of intelligent storage goods. The visual servo technology is used to obtain the objective constraints of the intelligent storage goods recognition function, and the greedy heuristic algorithm is used to solve the optimal intelligent storage goods recognition function to realise the intelligent storage goods classification and recognition. The experimental results show that the classification and recognition accuracy of intelligent storage goods can reach 96.3, the classification and recognition accuracy can reach 97.2%, and the efficiency is significantly improved.

Suggested Citation

  • Jinbin Zhao & Liyu Ma & Fei Gao & Shujian Chen, 2023. "Classification and recognition method of intelligent storage goods based on visual servo," International Journal of Manufacturing Technology and Management, Inderscience Enterprises Ltd, vol. 37(3/4), pages 391-403.
    • Handle: RePEc:ids:ijmtma:v:37:y:2023:i:3/4:p:391-403
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