LIN Bin, ZHANG Yan-bin, CHEN Shan-gong. Damage detection of engineering ceramics ground surface based on NMF[J]. Editorial Office of Optics and Precision Engineering, 2012,20(11): 2459-2464
LIN Bin, ZHANG Yan-bin, CHEN Shan-gong. Damage detection of engineering ceramics ground surface based on NMF[J]. Editorial Office of Optics and Precision Engineering, 2012,20(11): 2459-2464 DOI: 10.3788/OPE.20122011.2459.
Damage detection of engineering ceramics ground surface based on NMF
As the surface damage detection plays an important role in evaluating engineering ceramic surface quality
this paper introduces an image reconstruction algorithm
Nonnegative Matrix Factorization (NMF) algorithm
into the damage detection of engineering ceramics grounding surface for the first time. It analyzes the theoretical function of the algorithm and gives a detection example. First
the input image data set was reduced from an original data space to a lower-dimensional NMF space
and the image reconstruction relative error 0.1 rule proposed by this paper was used to determine a proper space basis
r
value. Then
the background image of ground texture was obtained by image reconstruction using two lower-dimensional nonnegative matrixes
and the ground textures were removed by image subtraction. Finally
the Canny edge detection was used to extract the damage image of engineering ceramics grounding surface. Experimental results indicate that the proposed method can accurately extract the surface damage of engineering ceramics and can calculate the evaluation parameter of grinding damage rate.
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ZHANG B,ZHENG X L,TOKURA H,et al.. Grinding induced damage in ceramics [J]. Journal of Materials Processing Technology, 2003, 132: 353-364.[2] KUMAR A. Computer-vision-based fabric defect detection: a survey [J]. IEEE Trans Ind Electron, 2008, 55(1): 348-363.[3] XIE X. A review of recent advances in surface defect detection using texture analysis techniques [J]. Electron Lett Comput Vis Image Anal, 2008, 7(3): 1-22.[4] GUILLAMET D,VITRI J. Non-negative matrix factorization for face recognition [J]. Lect Notes Comput Sci, 2002, 2504: 336-344.[5] LEE D D,SEUNG H S. Learning the parts of objects by non-negative matrix factorization [J]. Nature, 1999, 401(10): 788-791.[6] GUILLAMET D,VITRIA J,SCHIELE B. Introducing a weighted non-negative matrix factorization for image classification [J]. Int Conf Pattern Recognit, 2002, 2: 116-119.[7] GUILLAMET D,VITRI J,SCHIELE B. Introducing a weighted non-negative matrix factorization for image classification [J]. Pattern Recognition Letters, 2003, 24: 2447-2454.[8] 高涛,何明一. 改进投影梯度非负矩阵分解的单训练样本特征提取研究[J]. 电子与信息学报, 2010, 32(5): 1121-1125. GAO T,HE M Y. Using improved non-negative matrix factorization with projected gradient for single-trial feature extraction [J]. Journal of Electronics & Information Technology, 2010, 32(5): 1121-1125. (in Chinese)[9] 王梁,郝燕玲,张振兴. 基于NMF闭塞字典的压缩传感声纳图像识别[J]. 华中科技大学学报:自然科学版, 2011, 39(9): 29-33. WANG L,HAO Y L,ZHANG ZH X. Sonar image recognition of compressed sensing using NMF occlusion dictionary [J]. J. Huazhong Univ. of Sci. & Tech.:Natural Science Edition, 2011, 39(9): 29-33. (in Chinese)[10] LEE D D,SEUNG H S. Algorithms for non-negative matrix factorization [J]. Adv Neural Inf Process Syst, 2001, 13: 556-562.[11] 李乐,章毓晋. 基于线性投影结构的非负矩阵分解[J]. 自动化学报, 2010, 36(1): 23-39. LI L, ZHANG Y J. Linear Projection-based Non-negative Matrix Factorization [J]. Acta Automatica Sinica, 2010, 36(1): 23-39. (in Chinese)[12] GONG P H, ZHANG C S. Efficient nonnegative matrix factorization via projected newton method [J]. Pattern Recognition, doi:10.1016/j.patcog.2012.02.037.[13] LIN C J. Projected gradient methods for non-negative matrix factorization [J]. Neural Comput, 2007, 19(10): 2756-277.[14] 张俊雄,苟一,李伟. 基于形态特征的玉米种子表面裂纹检测方法[J]. 光学 精密工程, 2007,15(6): 951-956. ZHANG J X,GOU Y,LI W. Detection of surface cracks of corn kernel based on morphology [J]. Opt. Precision Eng., 2007, 15(6): 951-956. (in Chinese)