ArticleFrontiers in plant science2022
Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding.
Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A review of ultrasound monitoring applications in agriculture.Frontiers in plant science · 2025Review
- Detection and classification of surface defects on hot-rolled steel using vision transformers.Heliyon · 2024Article
- Efficient online detection device and method for cottonseed breakage based on Light-YOLO.Frontiers in plant science · 2024Article
- Intelligent Optimization Design of a Phononic Crystal Air-Coupled Ultrasound Transducer.Materials (Basel, Switzerland) · 2023Article
- Integrating spectral and image information for prediction of cottonseed vitality.Frontiers in plant science · 2023Article
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Authors and funding
7 authors.
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Abstract
Slight crack of cottonseed is a critical factor influencing the germination rate of cotton due to foamed acid or water entering cottonseed through testa. However, it is very difficult to detect cottonseed with slight crack using common non-destructive detection methods, such as machine vision, optical spectroscopy, and thermal imaging, because slight crack has little effect on morphology, chemical substances or temperature. By contrast, the acoustic method shows a sensitivity to fine structure defects and demonstrates potential application in seed detection. This paper presents a novel method to detect slightly cracked cottonseed using air-coupled ultrasound with a light-weight vision transformer (ViT) and a sound-to-image encoding method. The echo signal of air-coupled ultrasound from cottonseed is obtained by non-contact and non-destructive methods. The intrinsic mode functions (IMFs) of ultrasound signal are obtained as the sound features using variational mode decomposition (VMD) approach. Then the sound features are converted into colorful images by a color encoding method. This method uses different colored lines to represent the changes of different values of IMFs according to the specified encoding period. A light-weight MobileViT method is utilized to identify the slightly cracked cottonseeds using encoding colorful images corresponding to cottonseeds. The experimental results show an average overall recognition accuracy of 90.7% for slightly cracked cottonseed from normal cottonseed, which indicates that the proposed method is reliable to applications in detection task of cottonseed with slight crack.
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