Image processing to identify damage to soybean seeds
ABSTRACT: In Brazil and worldwide, commercialization of soybeans is of great importance to the economy, making their quality considered. The presence of damaged soybean seeds decreases the added value of the product. Businesses need fast and effective techniques to maintain the quality. The present research aimed to identify, through image processing, damage caused to soybean seeds, namely the presence of greenish seeds and wrinkled seeds due to variations of humidity and temperature, where it was possible to identify greenish and wrinkled soybean seeds from images. Results obtained for greenish seeds indicated that the red color scale is the most suitable for selection due to its more significant variation compared to the other color scales. For the separation of wrinkled seeds, it can be stated that it is possible to find a selection parameter with 74.3% accuracy in removing seeds with medium to high degrees of wrinkle damage.
| Main Authors: | , , , , |
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| Format: | Digital revista |
| Language: | English |
| Published: |
Universidade Federal de Santa Maria
2021
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| Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782021000200202 |
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| Summary: | ABSTRACT: In Brazil and worldwide, commercialization of soybeans is of great importance to the economy, making their quality considered. The presence of damaged soybean seeds decreases the added value of the product. Businesses need fast and effective techniques to maintain the quality. The present research aimed to identify, through image processing, damage caused to soybean seeds, namely the presence of greenish seeds and wrinkled seeds due to variations of humidity and temperature, where it was possible to identify greenish and wrinkled soybean seeds from images. Results obtained for greenish seeds indicated that the red color scale is the most suitable for selection due to its more significant variation compared to the other color scales. For the separation of wrinkled seeds, it can be stated that it is possible to find a selection parameter with 74.3% accuracy in removing seeds with medium to high degrees of wrinkle damage. |
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