表面等离子体共振后焦面吸收谱识别方法研究
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摘要
表面等离子体共振(SPR)技术作为一种检测方法,具有高精度和高实时性的特点。基于表面等离子体共振检测系统,通过识别表面等离子体共振后焦面图像中的吸收谱,检测材料特性。吸收谱识别方法主要是手动勾画或一维灰度统计,这2种方法均无法在强噪声背景下对大批量后焦面图像进行有效识别。针对这一问题,基于霍夫变换、形态学与最小二乘法,提出了一种高效的吸收谱识别方法,在含有强噪声的表面等离子共振后焦面图像识别问题中有着很好的表现。这种方法弥补了现有方法的不足,为表面等离子体共振后焦面吸收谱识别问题提供了一种全新的思路。
Surface plasmon resonance(SPR) technology is a detection method with high precision and high real-time characteristics. A surface plasmon resonance-based detection system detects material properties by identifying an absorption spectrum in a surface plasmon resonance back focal plane image. The absorption spectrum identification method is realized mainly by manual drawing or one-dimensional gray scale statistics. These two methods can 't effectively identify large-scale back focal plane images under strong noise background. To solve this problem, this paper proposes a high-efficiency absorption spectrum identification method based on Hough transform, morphology and least squares method, which has good performance in the image recognition problem of focal plane after plasmon resonance with strong noise. This method makes up for the shortcomings of existing methods and provides a new idea for the absorption spectrum identification of surface plasmon resonance.
Surface plasmon resonance(SPR) technology is a detection method with high precision and high real-time characteristics. A surface plasmon resonance-based detection system detects material properties by identifying an absorption spectrum in a surface plasmon resonance back focal plane image. The absorption spectrum identification method is realized mainly by manual drawing or one-dimensional gray scale statistics. These two methods can 't effectively identify large-scale back focal plane images under strong noise background. To solve this problem, this paper proposes a high-efficiency absorption spectrum identification method based on Hough transform, morphology and least squares method, which has good performance in the image recognition problem of focal plane after plasmon resonance with strong noise. This method makes up for the shortcomings of existing methods and provides a new idea for the absorption spectrum identification of surface plasmon resonance.
引文
[1]施玉佳,王凯.表面等离子体共振生物传感器综述[J].新丝路,2016(12):217.
[2]刘小桃.表面等离子体共振技术在环境污染物监测中的应用研究[J].低碳世界,2016(9):19-20.
[3]KRETSCHMANN E,RAETHER H.Radiative decay of non radiative surface plasmons excited by light[J].Zeitschrift für naturforschung A,1968,23(12):2135-2136.
[4]KANO H.Excitation of surface plasmon polaritons by a focused laser beam[M]//KAWATA S.Near-Field Optics and Surface Plasmon Polaritons.Berlin,Heidelberg:Springer,2001:189-206.
[5]王毅,胡永奇,张庆文.一种基于表面等离子体共振的光学显微镜[P].中国:CN105628655A,2016-06-01.
[6]SOMEKH M G,STABLER G,LIU Shugang,et al.Widefield high-resolution surface-plasmon interference microscopy[J].Optics letters,2009,34(20):3110-3112.
[7]龙建武,申铉京,陈海鹏.自适应最小误差阈值分割算法[J].自动化学报,2012,38(7):1134-1144.
[8]DUDA R O,HART P E.Use of the Hough transformation to detect lines and curves in pictures[J].Communications of the ACM,1972,15(1):11-15.
[9]ILLINGWORTH J,KITTLER J.A survey of the Hough transform[J].Computer vision,graphics,and image processing,1988,44(1):87-116.
[10]屈汉章,王洋,吴成茂.基于直径累积的霍夫变换检测圆算法[J].西安邮电大学学报,2017,22(5):89-93.
[11]HINTON E,CAMPBELL J S.Local and global smoothing of discontinuous finite element functions using a least squares method[J].International journal for numerical methods in engineering,1974,8(3):461-480.
[2]刘小桃.表面等离子体共振技术在环境污染物监测中的应用研究[J].低碳世界,2016(9):19-20.
[3]KRETSCHMANN E,RAETHER H.Radiative decay of non radiative surface plasmons excited by light[J].Zeitschrift für naturforschung A,1968,23(12):2135-2136.
[4]KANO H.Excitation of surface plasmon polaritons by a focused laser beam[M]//KAWATA S.Near-Field Optics and Surface Plasmon Polaritons.Berlin,Heidelberg:Springer,2001:189-206.
[5]王毅,胡永奇,张庆文.一种基于表面等离子体共振的光学显微镜[P].中国:CN105628655A,2016-06-01.
[6]SOMEKH M G,STABLER G,LIU Shugang,et al.Widefield high-resolution surface-plasmon interference microscopy[J].Optics letters,2009,34(20):3110-3112.
[7]龙建武,申铉京,陈海鹏.自适应最小误差阈值分割算法[J].自动化学报,2012,38(7):1134-1144.
[8]DUDA R O,HART P E.Use of the Hough transformation to detect lines and curves in pictures[J].Communications of the ACM,1972,15(1):11-15.
[9]ILLINGWORTH J,KITTLER J.A survey of the Hough transform[J].Computer vision,graphics,and image processing,1988,44(1):87-116.
[10]屈汉章,王洋,吴成茂.基于直径累积的霍夫变换检测圆算法[J].西安邮电大学学报,2017,22(5):89-93.
[11]HINTON E,CAMPBELL J S.Local and global smoothing of discontinuous finite element functions using a least squares method[J].International journal for numerical methods in engineering,1974,8(3):461-480.