IMPROVEMENT OF THE SORTING PROCESS USING A COMPUTER VISION SYSTEM AND A LIGHT SENSOR IN SORTING AGRICULTURAL PRODUCTS
Authors/Creators
- 1. PhD, Associate Professor, Bukhara State Technical University
- 2. PhD student, Bukhara State Technical University
Description
This article considers the issue of improving the sorting process of agricultural products, in particular fruits and vegetables. Due to the low accuracy and subjectivity of traditional sorting methods, the need to use modern technologies is justified. The study proposes an integrated approach to determine the external characteristics of products (color, shape, size) using a computer vision system and to evaluate internal quality indicators (ripeness, chemical composition) using near-infrared (NIR) spectroscopy.
Also, a statistical selection method and a prediction model based on PLS and SVM algorithms were developed for evaluating product groups. The proposed system allows to improve the quality of export-oriented products, automate the sorting process and reduce the human factor. As a result, the sorting accuracy increases, the export of low-quality products decreases, and the overall production efficiency increases.
Files
999-1005.pdf
Additional details
References
- S. Lorente, N. Aleixos, J. Gómez-Sanchis "Recent advances and applications of hyperspectral imaging for fruit and vegetable quality assessment", Food Engineering Reviews, 2012.
- H. Lu, Y. Peng " Prediction of apple firmness and soluble solids content using NIR spectroscopy", Journal of Food Engineering, 2006.
- AK Jain, MN Murty, PJ Flynn " Data clustering: A review", ACM Computing Surveys, 1999.
- Bhargava, A. (2021). Fruits and vegetables quality evaluation using computer vision. Journal of Food Engineering.
- Feng, J., Zhang, Y., & Liu, H. (2024). Real-time fruit and vegetable quality detection technologies. International Journal of Agricultural Engineering.