| Autor: |
DING Can, WANG Wen-sheng, HUANG Xiao-long |
| Jazyk: |
English<br />Chinese |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Liang you shipin ke-ji, Vol 32, Iss 4, Pp 178-184 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1007-7561 |
| DOI: |
10.16210/j.cnki.1007-7561.2024.04.022 |
| Popis: |
The aflatoxin produced by peanut mildew is highly carcinogenic, and it seriously affects food safety. In order to accurately and quickly identify moldy peanuts, this project proposes a detection method for moldy peanuts based on machine vision. Firstly, the peanut image was double-sided filtering and noise reduction, and then the image was converted to HSV space. The moldy peanut was recognized and detected by superimposing the mold color range extracted in H and S space and the open processing results of V space. The experimental results showed that the recognition accuracy of this method for moldy peanuts reached 95.3%, and the processing time for a single frame of peanut image was 0.6 seconds. Compared with other algorithms, this method had the advantages of fast speed and high accuracy, which can meet the real-time detection of moldy peanuts. At the same time, the grading processing of peanut mold is also more practical. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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