<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In developing robots for warehouse logistics, image recognition and processing for moving targets are the cornerstone of subsequent work. In this paper, the Meanshift algorithm is extended to continuous image sequences, and the Camshift algorithm for motion target tracking in a warehouse environment is proposed to obtain effective tracking of targets through the probability distribution when the color of continuous images changes dynamically. Based on target tracking, a feature-matching-based image recognition method is constructed. The scene image is first treated with improved Gamma correction for light equalization, and then image features are extracted using SURF feature points. Regarding running time, the feature matching method is, on average, 2.03 seconds faster than FLDA and 0.96 seconds faster than PCAFLDA under the same external conditions. By optimizing the computational structure, the feature-matching method can address the need for efficiency in warehouse logistics.</p>
</abstract>

In developing robots for warehouse logistics, image recognition and processing for moving targets are the cornerstone of subsequent work. In this paper, the Meanshift algorithm is extended to continuous image sequences, and the Camshift algorithm for motion target tracking in a warehouse environment is proposed to obtain effective tracking of targets through the probability distribution when the color of continuous images changes dynamically. Based on target tracking, a feature-matching-based image recognition method is constructed. The scene image is first treated with improved Gamma correction for light equalization, and then image features are extracted using SURF feature points. Regarding running time, the feature matching method is, on average, 2.03 seconds faster than FLDA and 0.96 seconds faster than PCAFLDA under the same external conditions. By optimizing the computational structure, the feature-matching method can address the need for efficiency in warehouse logistics.

Research on image recognition and processing of motion targets of warehouse logistics robots

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In developing robots for warehouse logistics, image recognition and processing for moving targets are the cornerstone of subsequent work. In this paper, the...

Research on image recognition and processing of motion targets of warehouse logistics robots

Online veröffentlicht: 01. Nov. 2023

Seitenbereich: -

Eingereicht: 28. Nov. 2022

Akzeptiert: 12. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00917

Schlüsselwörter
Image recognition, Camshift algorithm, Gamma correction, SURF feature points, Motion targets, Warehouse logistics

© 2023 Aodong Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on image recognition and processing of motion targets of warehouse logistics robots

Online veröffentlicht: 01. Nov. 2023

Seitenbereich: -

Eingereicht: 28. Nov. 2022

Akzeptiert: 12. Mai 2023

DOI: https://doi.org/10.2478/amns.2023.2.00917

SchlüsselwörterImage recognition, Camshift algorithm, Gamma correction, SURF feature points, Motion targets, Warehouse logistics

© 2023 Aodong Zhao et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Image recognition, Camshift algorithm, Gamma correction, SURF feature points, Motion targets, Warehouse logistics