期刊文献+

羽毛杆折痕自动识别方法 被引量:1

Method of automatic recognition for feather quill crease
下载PDF
导出
摘要 提出了一种羽毛杆折痕检测方法。将羽毛杆图像转化为一维信号,利用小波变换模极大值和信号奇异点的关系完成折痕位置预判,通过该位置完成子图像提取,减少对羽毛杆遍历检测带来的误判;提出局部Radon变换计算子图像不变矩,通过改变尺度因子获得矩不变量矩阵,利用奇异值分解获得特征量;采用决策级融合方法得到最终识别结果。实验结果表明,该方法有着较低的非折痕误测率和较高的折痕识别率,适用于羽毛杆表面缺陷的自动识别。 A detection method of feather quill crease is proposed. The feather quill image is transformed into one dimensional signal, using the relationship between wavelet transform modulus maxima and singular point, the crease coordinate is prejudged. Subimage is extracted through the coordinate to reduce misiudgeement caused by image traversal. With local Radon transform to extract moment invariants of target subimage, invariants matrix is obtained by changing the scale factor, singular value decomposition is provided to obtain feature invariant for recognition. Finally, the final recognition result of the system is achieved by the fusion of identification results at the decision level. The results show that this suggested method has high recognition rate and is applicable to recognition of feather quill.
出处 《计算机工程与设计》 CSCD 北大核心 2013年第12期4351-4355,共5页 Computer Engineering and Design
基金 广东省科技计划基金项目(2012B020314005)
关键词 羽毛杆折痕 模极大值 局部Radon变换 矩不变量 奇异值分解 feather quill crease modulus maxima local Radon transform moment invariants SVD
  • 相关文献

参考文献10

二级参考文献74

共引文献88

同被引文献13

  • 1Zernike F. Beugungstheorie des schneidenver -fahrens und seiner verbesserten form, der phasenkontrastmethode [ J ]. Physica, 1934, 1(7): 689-704.
  • 2Khotanzad A, Hong Y H. Invariant image recognition by Zernike moments[ J]. Pattern Analysis and Machine Intelli- gence, IEEE Transactions on, 1990, 12(5) : 489 -497.
  • 3Hosny K M, Papakostas G A, Koulouriotis D E. Accurate reconstruction of noisy medical images using orthogonal mo- ments[C]//Digital Signal Processing (DSP), 2013 18th International Conference on. IEEE, 2013 : 1 -6.
  • 4Kulkami A H, Rai H M, Jahagirdar K A, et al. A Leaf Recognition System for Classifying Plants Using RBPNN and pseudo Zernike Moments [ J ]. International Journal of Latest Trends in Engineering and Technology, 2013, 2( 1 ) : 6 -10.
  • 5Salouan R, Safi S, Bouikhalene B. A Comparative Study between the Pseudo Zernike and Krawtchouk Invariants Mo- ments for Printed Arabic Characters Recognition[ J ]. Jour- nal of Emerging Technologies in Web Intelligence, 2014, 6 (1):1 -7.
  • 6Khotanzad A, Hong Y H. Invariant image recognition by Zernike moments [ J ]. Pattern Analysis and Machine Intelli- gence, IEEE Transactions on, 1990, 12(5) : 489 -497.
  • 7Cortes C, Vapnik V. Support-vector networks [ J ]. Ma- chine learning, 1995, 20(3) : 273 -297.
  • 8Teh C H, Chin R T. On image analysis by the methods of moments [ J ]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1988, 10(4) : 496 -513.
  • 9刘洪江,汪仁煌,李学聪.毛杆图像的一种灰度校正算法[J].广东工业大学学报,2010,27(1):47-50. 被引量:1
  • 10刘洪江,汪仁煌.基于羽毛图像纹理分割的毛杆提取方法[J].广东工业大学学报,2010,27(4):42-45. 被引量:5

引证文献1

二级引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部