Detection of bruised yellow peach using hyperspectral imaging combined with curvature-assisted Hough transform circle detection and improved Otsu

被引:0
|
作者
Li, Bin [1 ]
Su, Cheng-Tao [1 ]
Yin, Hai [1 ]
Ou-Yang, Ai-Guo [1 ]
Liu, Yan-De [1 ]
机构
[1] East China Jiaotong Univ, Sch Mechatron Engn, Nanchang 330013, Peoples R China
关键词
Hyperspectral; Bruising; Yellow peach; Band ratio; Improved Otsu; MECHANICAL DAMAGE; REFLECTANCE; FRUIT; MUSHROOMS; APPLES; DECAY;
D O I
10.1007/s11694-024-02541-7
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
The quality of yellow peaches was severely reduced due to bruising. Detection of bruised areas in yellow peach is easily disturbed by the calyx and stem ends. Therefore, it is proposed to utilize hyperspectral imaging in conjunction with I-Otsu in the detection of bruise detection in yellow peach after distinguishing between calyx and stem end using curvature-assisted Hough transform circle detection. The band ratio was used to improve the contrast of the images, and the improved Otsu method was used to improve the segmentation accuracy. Noise in the image is eliminated by adaptive median filtering. The effects of the calyx and stem ends are eliminated by curvature-assisted Hough transform circle detection. Spectral bands with valid feature information were selected by principal component analysis and key single-wavelength images (452.8 nm, 608.9 nm, 671.8 nm, 689.4 nm, 825.7 nm, and 966.2 nm) were selected from the loading curves of the spectral regions to create PC images and band ratio images. Band ratio (Q608.9/689.4) images with I-Otsu were used to segment the bruise region. Ultimately, 96% of the bruised yellow peaches were correctly identified. This study demonstrates that hyperspectral imaging combined curvature-assisted Hough transform circle detection and I-Otsu can accurately identify bruised areas as well as calyx and stem ends in yellow peach.
引用
收藏
页码:4865 / 4878
页数:14
相关论文
共 50 条
  • [21] A proposed circle/circular arc detection method using the modified randomized hough transform
    Chiu, Shih-Hsuan
    Liaw, Jiun-Jian
    [J]. JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS, 2006, 29 (03) : 533 - 538
  • [22] HOUGH-TRANSFORM-BASED CIRCLE DETECTION USING AN ARRAY OF MULTIMODE OPTICAL FIBERS
    LI, Y
    EICHMANN, G
    [J]. OPTICS COMMUNICATIONS, 1987, 61 (04) : 248 - 251
  • [23] ISAR imaging of multiple targets using edge detection and Hough transform
    Park, S. H.
    Park, K. K.
    Jung, J. H.
    Kim, H. T.
    Kim, K. T.
    [J]. JOURNAL OF ELECTROMAGNETIC WAVES AND APPLICATIONS, 2008, 22 (2-3) : 365 - 373
  • [24] A Real-time Double Emulsion Droplets Detection System using Hough Circle Transform and Color Detection
    Zhu, Shuo
    Li, Chunxu
    Rogers, James
    Gianni, Mario
    Howard, Ian
    [J]. 2021 27TH INTERNATIONAL CONFERENCE ON MECHATRONICS AND MACHINE VISION IN PRACTICE (M2VIP), 2021,
  • [25] Detection and Counting of Red Blood Cells in Human Urine using Canny Edge Detection and Circle Hough Transform Algorithms
    Caya, Meo Vincent
    Padilla, Dionis
    Ombay, Gilbert
    Hernandez, Arnold Janssen
    [J]. 2019 IEEE 11TH INTERNATIONAL CONFERENCE ON HUMANOID, NANOTECHNOLOGY, INFORMATION TECHNOLOGY, COMMUNICATION AND CONTROL, ENVIRONMENT, AND MANAGEMENT (HNICEM), 2019,
  • [26] Efficient randomized Hough transform for circle detection using novel probability sampling and feature points
    Jiang, Lianyuan
    [J]. OPTIK, 2012, 123 (20): : 1834 - 1840
  • [27] Fast road sign detection using hough transform for assisted driving of road vehicles
    García-Garrido, MA
    Sotelo, MA
    Martín-Gorostiza, E
    [J]. COMPUTER AIDED SYSTEMS THEORY - EUROCAST 2005, 2005, 3643 : 543 - 548
  • [28] Robust lane detection and tracking using improved Hough transform and Gaussian Mixture Model
    Zhang, Yun
    Gong, Junbin
    Tian, Jinwen
    [J]. MIPPR 2011: AUTOMATIC TARGET RECOGNITION AND IMAGE ANALYSIS, 2011, 8003
  • [29] Visual Detection of SSC and Firmness and Maturity Prediction for Feicheng Peach by Using Hyperspectral Imaging
    Shao, Yuanyuan
    Wang, Yongxian
    Xuan, Guantao
    Gao, Chong
    Wang, Kaili
    Gao, Zongmei
    [J]. Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2020, 51 (08): : 344 - 350
  • [30] Detection of Chili Foreign Objects Using Hyperspectral Imaging Combined with Chemometric and Target Detection Algorithms
    Shu, Zhan
    Li, Xiong
    Liu, Yande
    [J]. FOODS, 2023, 12 (13)