不同光照下织物瑕疵检测方法研究
Research on Fabric Defects Detect Methods under Different Illumination
DOI: 10.12677/CSA.2014.49026, PDF, HTML, 下载: 2,795  浏览: 6,377 
作者: 张国英, 陈淑兰, 赵 君:中国矿业大学(北京),机电与信息工程学院,北京
关键词: 瑕疵检测织物纹理不同光照傅里叶?极坐标变换能量统计Defect Detection Fabric Texture Different Illumination Fourier-Polar Axis Transform Energy Statistic
摘要: 本文研究的目的是检测不同光照下纺织工业中织布的瑕疵,不同光照下的织布图像清晰度不同,但却都非常有周期性,有方向性。所以本文提出了一种基于傅里叶极坐标变换的方法:该方法将图像在频域内的频谱能量转化到极坐标中,在极坐标中统计同一角度的能量值总和找到织布图像纹理主方向。降低该方向能量,可增强瑕疵的突出性。实验证明,该方法检测织物瑕疵准确率高可以满足不同光照下的实时检测要求。
Abstract: This paper aims to detect the defect of fabric under different illumination in texture industry. Al-though the definitions of fabric images are different under different illumination, they all have strong cyclicity and directionality. So a detection method is presented based on Fourier-polar coordinate processing in this paper. In frequency domain, the spectrum energy is transformed to the polar coordinate. Then in the polar coordinate, the sum of energy is added up at the same angle, and the main direction of image texture is found according to the energy sum. Salience of defect is enhanced by lowering the energy on the main direction. Experiments show that the method for detecting fabric defects with high accuracy can meet the requirements of real-time detection under different illumination.
文章引用:张国英, 陈淑兰, 赵君. 不同光照下织物瑕疵检测方法研究[J]. 计算机科学与应用, 2014, 4(9): 181-186. http://dx.doi.org/10.12677/CSA.2014.49026

参考文献

[1] 章毓晋 (2001) 图像分割. 科学出版社, 北京.
[2] 韩思奇, 王蕾 (2002) 图像分割的阈值法综述. 系统工程与电子技术, 6, 91-94.
[3] Haralick, R., Shanmugam, K. and Dinstein, I. (1973) Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics, 23, 610-621.
[4] Unser, M. and Ade, F. (1984) Feature extraction and decision procedure for automated inspection of textured materials. Pattern Recognition, 2, 185-191.
[5] Tsai, D.M. and Hsieh, C.Y. (1999) Automated surface inspection for directional textures. Image and Vision Computing, 18, 49-62.
[6] Kumar, A. and Pang, G.K.H. (2002) Defect detection in textured materials using Gabor filters. IEEE Transactions on Industry Applications, 38, 425-440.
[7] 孙自广, 何春华, 唐培和, 等 (2010) 基于小波纹理特征的织物疵点检测. 计算机测量与控制, 9, 111-113.
[8] Gonzalez, R.C. and Woods, R.E. (2011) Digital Image Processing. 3rd Edition, Prentice Hall Press, Upper Saddle River, 540.
[9] 张轶 (2004) 实时布匹瑕疵检测技术研究. 硕士论文, 天津工业大学, 天津.
[10] 刘万春, 罗双华, 朱玉文, 等 (2004) 基于聚类分析和支持向量机的布匹瑕疵分类方法. 北京理工大学学报, 8, 33-36.
[11] 张兴烨 (2012) 织物疵点自动检测系统关键技术的研究. 博士论文, 江南大学, 无锡.
[12] 李鑫, 许增朴, 于德敏, 等 (2008) 基于图像能量的布匹瑕疵检测方法. 计算机测量与控制, 9, 34-36.
[13] 周游, 庞全 (2012) 傅里叶频谱径角特征的植物相似性. 计算机系统应用, 11, 163-166.