• Spectroscopy and Spectral Analysis
  • Vol. 40, Issue 11, 3384 (2020)
Cui-ling LIU1、1、*, Shao-min WANG1、1, Jing-zhu WU1、1, and Xiao-rong SUN1、1
Author Affiliations
  • 1[in Chinese]
  • 11. School of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China
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    DOI: 10.3964/j.issn.1000-0593(2020)11-3384-06 Cite this Article
    Cui-ling LIU, Shao-min WANG, Jing-zhu WU, Xiao-rong SUN. Study on Internal Quality Nondestructive Detection of Sunflower Seed Based on Terahertz Time-Domain Transmission Imaging Technology[J]. Spectroscopy and Spectral Analysis, 2020, 40(11): 3384 Copy Citation Text show less
    Sample of sunflower seeds(a): Normal seed; (b): Damaged kernel; (c): Worm-eaten kernel; (d): Empty seed
    Fig. 1. Sample of sunflower seeds
    (a): Normal seed; (b): Damaged kernel; (c): Worm-eaten kernel; (d): Empty seed
    Experimental apparatus(a): Terahertz pulse spectrometer; (b): Terahertz transmission imaging attachment
    Fig. 2. Experimental apparatus
    (a): Terahertz pulse spectrometer; (b): Terahertz transmission imaging attachment
    Terahertz transmission images of four categories of sunflower seeds(a): Normal seed; (b): Damaged kernel; (c): Worm-eaten kernel; (d): Empty seed
    Fig. 3. Terahertz transmission images of four categories of sunflower seeds
    (a): Normal seed; (b): Damaged kernel; (c): Worm-eaten kernel; (d): Empty seed
    Time-domain spectra corresponding to different positions of sunflower seed
    Fig. 4. Time-domain spectra corresponding to different positions of sunflower seed
    Terahertz image filtering results of insect-eroded sunflower seeds(a): 5×5 template mean filtering;(b): 5×5 template median filtering; (c): NML filtering
    Fig. 5. Terahertz image filtering results of insect-eroded sunflower seeds
    (a): 5×5 template mean filtering;(b): 5×5 template median filtering; (c): NML filtering
    Results of morphological filtering of insect-eroded sunflower seeds terahertz image(a): Original image; (b): One dilatation result;(c): External gradient; (d): Morphological gradient
    Fig. 6. Results of morphological filtering of insect-eroded sunflower seeds terahertz image
    (a): Original image; (b): One dilatation result;(c): External gradient; (d): Morphological gradient
    Morphological filtering results of sunflower seed images with different states(a): Normal seed; (b): Damaged kernel;(c): Worm-eaten kernel; (d): Empty seed
    Fig. 7. Morphological filtering results of sunflower seed images with different states
    (a): Normal seed; (b): Damaged kernel;(c): Worm-eaten kernel; (d): Empty seed
    K-means image segmentation results of sunflower seed images with different states(a): Normal seed; (b): Damaged kernel;(c): Worm-eaten kernel; (d): Empty seed
    Fig. 8. K-means image segmentation results of sunflower seed images with different states
    (a): Normal seed; (b): Damaged kernel;(c): Worm-eaten kernel; (d): Empty seed
    Cui-ling LIU, Shao-min WANG, Jing-zhu WU, Xiao-rong SUN. Study on Internal Quality Nondestructive Detection of Sunflower Seed Based on Terahertz Time-Domain Transmission Imaging Technology[J]. Spectroscopy and Spectral Analysis, 2020, 40(11): 3384
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