• Laser & Optoelectronics Progress
  • Vol. 55, Issue 5, 051501 (2018)
Zerun Wang, Yiming Fang*, Hailin Feng, Xiaochen Du, and Kai Xia
Author Affiliations
  • School of Information Engineering, Zhejiang A & F University, Lin'an, Zhejiang 311300, China
  • show less
    DOI: 10.3788/LOP55.051501 Cite this Article Set citation alerts
    Zerun Wang, Yiming Fang, Hailin Feng, Xiaochen Du, Kai Xia. Method for Wooden Knot Detection and Localization[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051501 Copy Citation Text show less
    References

    [1] Zhou Z, Yin J X, Zhou S Y et al. Knot defection on coniferous wood surface by near infrared spectroscopy and successive projections algorithm[J]. Laser & Optoelectronics Progress, 54, 023001(2017).

    [2] Norlander R, Grahn J, Maki A. Wooden knot detection using convNet transfer learning[M]. Lecture Notes in Computer Science, 9127, 263-274(2015).

    [3] Ma X, Liu Y A, Ye N et al. Application of KPCA and SVM to wood defect recognition[J]. Journal of Changzhou University(Natural Science Edition), 29, 60-68(2017).

    [4] Song X Y, Bai F Z, Wu J X et al. Wood knot defects recognition with gray-scale histogram features[J]. Laser & Optoelectronics Progress, 52, 031501(2015).

    [5] Cetiner S, Var A A, Cetiner H. Classification of KNOT defect types[C]. Signal Processing and Communications Applications Conference, 1086-1089(2014).

    [6] Zhang Z, Ye N, Ye Q L. Automatic wood defects recognition based on texture extraction and support vector machine technology[J]. Computer Engineering and Applications, 45, 219-223(2009).

    [7] Lotfi A, Maihami V, Yaghmaee F. Wood image annotation using gabor texture feature[J]. International Journal of Mechatronics, Electrical and Computer Technology, 4, 1508-1523(2014). http://search.ricest.ac.ir/ricest/show12.aspx?Doc_ID=3607958

    [8] Cai R T, Zhu P. Face tracking with muli-feature based on Markov random field[J]. Laser & Optoelectronics Progress, 54, 021002(2017).

    [9] Zhang Y Z, Xu C, Li C et al. Wood defect detection method with PCA feature fusion and compressed sensing[J]. Journal of Forestry Research, 26, 745-751(2015). http://link.springer.com/article/10.1007/s11676-015-0066-4

    [10] Wu P. Image segmentation method based on firefly algorithm and maximum entropy method[J]. Computer Engineering and Applications, 50, 115-119(2014).

    [11] Ojala T, Pietikäinen M, Harwood D. A comparative study of texture measures with classification based on featured distributions[J]. Pattern recognition, 29, 51-59(1996). http://www.sciencedirect.com/science/article/pii/0031320395000674

    [12] Gao X J, Zheng X D, Liu Z X et al. Automatic building extraction from high resolution visible images based on shifted shadow analysis[J]. Acta Optica Sinica, 37, 0428002(2017).

    [13] Sammut C, Webb G I. Encyclopedia of machine learning[M]. New York: Springer Science & Business Media(2011).

    [14] Fawcett T. An introduction to ROC analysis[J]. Pattern Recognition Letters, 27, 861-874(2006). http://dl.acm.org/citation.cfm?id=1159475

    [15] Zhan Y J, Wang H M, Fu X H et al. Identification of steel plate damage position based on particle swarm support vector machine[J]. Chinese Journal of Lasers, 44, 1006006(2017).

    [16] Shi F, Wang X C, Yu L et al[M]. MATLAB neural network analysis of 30 cases(2011).

    Zerun Wang, Yiming Fang, Hailin Feng, Xiaochen Du, Kai Xia. Method for Wooden Knot Detection and Localization[J]. Laser & Optoelectronics Progress, 2018, 55(5): 051501
    Download Citation