Paper
28 April 2023 Research on sorting of waste beverage bottles based on HSV space color features
Haikun Ding, Jian Wu, Mingbo Ma
Author Affiliations +
Proceedings Volume 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022); 126260X (2023) https://doi.org/10.1117/12.2674658
Event: International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 2022, Zhuhai, China
Abstract
At present, our country's plastic industry is developing rapidly. When plastic products bring great convenience to people's lives, waste plastic waste also causes huge pollution to the environment. Sorting, in view of the problem that various colors of plastic bottles are mixed in the sorting of waste plastic bottles, and the sorting is more labor-intensive, which leads to the increase of recycling costs. This paper studies the denoising process and color feature extraction before image recognition of plastic bottles, using HSV The model replaces the RGB model for color feature extraction. The recognition rate of the HSV model is 96.67%, and the recognition rate of the RGB model is 95.00%, but the recognition speed of HSV is increased by 16.43%.
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Haikun Ding, Jian Wu, and Mingbo Ma "Research on sorting of waste beverage bottles based on HSV space color features", Proc. SPIE 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 126260X (28 April 2023); https://doi.org/10.1117/12.2674658
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KEYWORDS
RGB color model

Plastics

Color

Image processing

Feature extraction

Gaussian filters

Digital filtering

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