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草红花显微特征点的不变矩表达 被引量:11

Digital Description for Microscopic Characteristic Images of Flos Carthami with Invariant Moments
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摘要 本研究用变形雅可比(p=4,q=3)-傅立叶矩(PJFM’s),对草红花粉末涂片的花粉粒、分泌管碎片、花瓣细胞、花药中部细胞、花瓣顶端细胞、花柱头细胞等六个显微结构原始照片进行特征提取,发现不同特征点的不变矩值有着明显的区别,相同显微特征点不同方位、不同灰度、不同大小的变形图像的不变矩值几乎相同。并且通过重建实验,证明使用很少的PJFM’s就能很好地表达原始图像,且PJFM’s具有较强的自动抗噪声能力。PJFM’s可作为一种高度浓缩的图像特征,用于中药粉末显微特征快速自动识别系统的特征提取量。该研究结果为中药材显微识别和鉴定的数字化提供重要的技术基础。 Pseudo-Jacobi( p = 4, q = 3)-Fourier Moments ( PJFM' s) were applied to extract image featurs from six microscopic characteristic original photos of flos carthami, which included farina, fragment of secretory pipe, top cell of petal, petal cell, stigma cell, middle cell of anther in this paper. The experimental result indicated that the values of invariant moment were very different for different microscopic characteristic images and were nearly same for different versions of a microscopic characteristic image. The quality of reconstructed images also proved that PJFM' s were the highly condensed feature descriptor for image digitalization, and PJFM' s were also automatically robust to noise. This study may provide some technical basis for digitalization and visualization of Chinese herbal identification.
出处 《中国生物医学工程学报》 CAS CSCD 北大核心 2007年第2期220-225,共6页 Chinese Journal of Biomedical Engineering
基金 国家自然科学基金(60467001) 内蒙古自然科学基金(200408020109) 内蒙古自治区高等学校科学研究项目(NJ03037)
关键词 中草药 显微特征点 变形雅可比(p=4 q=3)-傅立叶矩 数字化 Chinese herbal microscopic characteristics Pseudo-Jacobi (p = 4, q = 3 )-Fourier Moments digitalization
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参考文献9

  • 1肖培根.新编中药志[M].北京:化学工业出版社,2002.201.
  • 2国家药典委员会.中华人民共和国药典[M].北京:化学工业出版社,2000.168.
  • 3Sheng Yunlong,Shen Lixin.Orthogonal Fourier-Mellin moments for invariant pattern recognition[J].J Opt Soc Am A,1994,11(6):1748-1757.
  • 4Ping Ziliang,Wu Rigen,Shen Yunlong.Image description with Chebyshev-Fourier moments[J].J Opt Soc Am A,2002,19(9):1748-1754.
  • 5Ren Haiping,Ping Ziliang,Bo Wurigen,et al.Multidistortioninvariant image recognition with radial harmonic Fourier moments[J].J Opt Soc Am A,2003,20(4):631-637.
  • 6任海萍,平子良,博午日亘,盛云龙.基于雅可比-傅里叶矩的细胞模式识别[J].中国生物医学工程学报,2005,24(5):531-534. 被引量:4
  • 7AmuGuleng(阿木古楞) HasiSurong(哈斯苏荣).Invariant Image Analysis by Pseudo—Jacobi—Fourier Moments[J].Applied Optics,2004,43(12).
  • 8阿木古楞,杨性愉,平子良.变形雅可比(p=4,q=3)-傅立叶矩的抗噪声能力研究[J].光电子.激光,2003,14(11):1191-1195. 被引量:14
  • 9阿木古楞,杨性愉,平子良.基于变形雅可比(p=4,q=3)-傅立叶矩的形状识别研究[J].模式识别与人工智能,2005,18(1):75-80. 被引量:6

二级参考文献36

  • 1M K Hu. Visual pattern recognition by moment invariants[J]. IRE Trans Inf Theory,1962,IT-8: 179-187.
  • 2M R Teague. Image analysis via the general theory of moments[J]. J Opt Soc Am, 1980,70(8) :920-930.
  • 3C H The,R T Chin. On image analysis by the methods of moments[J]. IEEE Trans Pattern Anal Mach Intell,1988,10(4) : 496-513.
  • 4Y L Sheng, L X Shen. Orthogonal Fourier-Mellin moments for invariant pattern recognition [J]. J Opt Soc Am,1994,A11(6) :1748-1757.
  • 5Z L Ping,R G Wu,Y L Sheng. Describing image with Chebyshev-Fourier Moments[J]. J Opt Soc Am, 2002, 19(9) : 1748-1754.
  • 6A Khotanzad, Y H Hong. Invariant image recognition by Zernike moments[J]. IEEE Trans Pattern Anal Mach.Intell, 1990,12(5) :489-497.
  • 7N Towghi,B Javidi. Optimum receivers for pattern recognition in the presence of Gaussian noise with unknown statistics[J]. J Opt Soc Am A ,2001 ,18(8) : 1844-1852.
  • 8Y L Sheng, H H Arsenault. Noisy-image normalization using low-order radial moments of circular-harmonic function[J]. J Opt Soc Am A, 1987,4(7) : 1176-1184.
  • 9B Wang,C C Sun. Enhancement of signal-to-noise ratio of a double random phase encoding encryption system[J].Opt Eng ,2001,40(8) : 1502-1506.
  • 10N Towghi, B Javidi. Generalized optimum receiver for pattern recognition with multiplicative, additive, and nonoverlapping background noise[J]. J Opt Soc Am A,1998,15(6) : 1557-1565.

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