Volume 4 Issue 1
Oct.  2023
Turn off MathJax
Article Contents
Chaoqing MIN, Shun YU, Guohua JIA, Dongdong LIU, Kedian WANG. Comprehensive defect detection of bamboo strips with new feature extraction machine vision methods[J]. Journal of Advanced Manufacturing Science and Technology , 2024, 4(1): 2023018. doi: 10.51393/j.jamst.2023018
Citation: Chaoqing MIN, Shun YU, Guohua JIA, Dongdong LIU, Kedian WANG. Comprehensive defect detection of bamboo strips with new feature extraction machine vision methods[J]. Journal of Advanced Manufacturing Science and Technology , 2024, 4(1): 2023018. doi: 10.51393/j.jamst.2023018

Comprehensive defect detection of bamboo strips with new feature extraction machine vision methods

doi: 10.51393/j.jamst.2023018
  • Received Date: 2023-09-08
  • Accepted Date: 2023-10-31
  • Rev Recd Date: 2023-10-18
  • Available Online: 2023-11-21
  • Publish Date: 2023-11-21
  • Bamboo strips, as assembling parts of sleeping mats, cushions and other decorative components, play an important role in humans’ everyday life and social economy now. Therefore, quality control for bamboo strips production is very critical. Traditional manual sorting technology owns many disadvantages such as high production cost and low sorting accuracy. This work deals with an automatic sorting system for comprehensive defect detection of bamboo strips based on machine vision. Differing from the present feature extraction methods of the bamboo strip in image processing, contour features considering area and geometrical symmetry and texture feature considering average gradient are newly introduced. An experimental automatic sorting system is designed to verify the feasibility and superiority of the proposed comprehensive defect detection method. Experimental results show that total defect detection accuracy, contour defect detection accuracy, surface texture defect detection accuracy and sorting accuracy reach 99.1%, 98.33%, 95.2% and 95.125%, respectively. The designed sorting system finishes one time sorting in 197 ms with a comparable low-speed computation processor in laboratory and it can be utilized instead of three skilled workers in practice.

  • loading
  • [1]
    . Wu JQ, Li ZY. International competitiveness of main bamboo and rattan commodities in China. Chinese Forestry Science and Technology 2009;8(2):55-62.
    [2]
    . Wang XY, Liang DT, Deng WY. Surface grading of bamboo strips using multi-scale color texture features in eigenspace. Computer and Electronics in Agriculture 2010; 73:91-98.
    [3]
    . Qin XS, Xin S, Liu Q. Online detection and sorting system of bamboo strip based on visual servo. International Conference on Industrial Technology; 2009.p.1-5.
    [4]
    . Tajeripour F, Kabir E, Sheikhi A. Fabric defect detection using modified local binary patterns. EURASIP Journal on Advances in Signal Processing 2008; 2008:1-12.
    [5]
    . Liao S, Law M, Chung A. Dominant local binary patterns for texture classification. IEEE Trans on Image Process 2009;18(5):1107-1118.
    [6]
    . Guo Z, Zhang L, Zhang D. A completed modeling of local binary pattern operator for texture classification. IEEE Trans on Image Process 2010;19(6):1657-1663.
    [7]
    . Zhang Y, Zhao Y, Liu Y, et al. Identification of wood defects based on LBP features. The 35th Chinese Control Conference; 2016.p.4202-4205.
    [8]
    . Ojala T, Pietikaeinen M, Harwood D. A comparative study of texture measures with classification based on feature distributions. Pattern Recognition 1996; 29(1):51-59.
    [9]
    . Haralick RM, Shanmugam K, Dinstein I. Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics 1973;3(6):610-621.
    [10]
    . Wang B, Wang H, Qi H. Wood recognition based on grey-level cooccurrence matrix. International Conference on Computer Application and System Modeling; 2010.p.269-272.
    [11]
    . Fahrurozi A, Madenda S, Ernastuti E, et al. Wood texture features extraction by using GLCM combined with various edge detection methods. Journal of Physics: Conference Series 2016; 725(1):012005.
    [12]
    . Mahram A, Shayesteh MG, Jafarpour S. Classification of wood surface defects with hybrid usage of statistical and textural features. The 35th International Conference on Telecommunications and Signal Processing; 2012.p.749-752.
    [13]
    . Kuang HL, Ding YR, Li RF, et al. Defect detection of bamboo strips based on LBP and GLCM features by using SVM classifier. The 30th Chinese Control and Decision Conference (CCDC); 2018.p.3341-3345.
    [14]
    . Colgan MS, Bladeck CA, Feret JB, et al. Mapping savanna tree species at ecosystem scales using support vector machine classification and BRDF correction on airborne hyperspectral and lidar data. Remote Sensing 2012; 4:3462-3480.
    [15]
    . Parveen AS. Detection of brain tumor in MRI images, using combination of fuzzy c-means and SVM. 2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN); 2015.p.98-102.
    [16]
    . Piuri V, Scotti F. Design of an automatic wood types classification system by using fluorescence spectra. IEEE Transactions on Systems, Man, and Cybernetics 2010; 40:3.
    [17]
    . Zhang P, Kai Z, Li ZW, et al. High dynamic range 3D measurement based on structured light: A review. Journal of Advanced Manufacturing Science and Technology 2021; 1(2): 2021004.
    [18]
    . Muruganatham C, Jawahar M, Ramamoorthy B. Optimal settings for vision camera calibration. The International Journal of Advanced Manufacturing Technology 2009; 42:736-748.
    [19]
    . Fu JH, Liu HD, He MQ, et al. A hand-eye calibration algorithm of binocular stereo vision based on multi-pixel 3D geometric centroid relocalization. Journal of Advanced Manufacturing Science and Technology 2022; 2(1): 2022005.
    [20]
    . Erkan U, Goekrem L, Enginoglu S. Different applied median filter in salt and pepper noise. Computers & Electrical Engineering 2018; 28:241-253.
    [21]
    . Javadpour A, Mohammadi A. Improving brain magnetic resonance image (MRI) segmentation via a novel algorithm based on genetic and regional growth. Journal of Biomedical Physics and Engineering 2016; 6(2):95-108.
    [22]
    . Ojala T, Pietikaeinen M, Maenpaeae T. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Anal 2002; 24(7):971-987.
    [23]
    . Ulaby FT, Kouyate F, Brisco B. Textural information in SAR images. IEEE Transactions on Geoscience and Remote Sensing 1986; 24(2):235-245.
    [24]
    . Pei Z, Zhang H. Visual object matching based on gradient ICA feature. International Symposium on Computer Science and Computational Technology; 2008.p.159-162.
    [25]
    . Chaple GN, Daruwala RD, Gofane MS. Comparisions of Robert, Prewitt, Sobel operator based edge detection methods for real time uses on FPGA. International Conference on Technologies for Sustainable Development (ICTSD); 2015.p.1-4.
    [26]
    . Chang CC, Lin CJ. Libsvm: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology 2007; 2(3):1-30.
    [27]
    . Fawcett T. An introduction to ROC analysis. Pattern Recognition Letters 2006; 27(8):861-874.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)

    Article Metrics

    Article views (325) PDF downloads(27) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return