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

Authors: Jinbin Zhao; Liyu Ma; Fei Gao; Shujian Chen

Addresses: Beijing Institute of Remote Sensing Information, Beijing 100011, China ' Beijing Institute of Remote Sensing Information, Beijing 100011, China ' Beijing Institute of Remote Sensing Information, Beijing 100011, China ' Beijing Institute of Remote Sensing Information, Beijing 100011, China

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.

Keywords: visual servoing; quaternion Gabor filter convolution algorithm; greedy heuristic algorithm; intelligent storage; cargo classification and recognition.

DOI: 10.1504/IJMTM.2023.133478

International Journal of Manufacturing Technology and Management, 2023 Vol.37 No.3/4, pp.391 - 403

Received: 11 Feb 2022
Received in revised form: 22 Mar 2022
Accepted: 05 Jul 2022
Published online: 17 Sep 2023 *

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