改进的人工鱼群算法在显微镜自动对焦中的应用
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摘要
对焦窗口的选择是实现显微镜自动对焦的关键步骤。针对传统的对焦窗口选取方法不能准确定位目标物体的问题,本文提出了一种改进的人工鱼群对焦窗口法。以整幅图像中细节最丰富的区域作为对焦窗口的选取依据,充分利用人工鱼群算法良好的全局寻优能力,在整幅图像中选取最佳对焦窗口;将全局优值添加到每条人工鱼的行为更新中,使其能快速移动到当前最佳位置甚至是全局最优位置。此外,在算法中引入了淘汰机制,在保证精度的前提下,提高算法的收敛速度;再根据算法中公告板的特点,结合趋势对比法识别干扰区域,有效排除非目标区域的影响。实验表明,该方法得到的对焦窗口,可以更好地对目标物体进行对焦,大大提高了自动对焦的精确度,并且构建对焦窗口的效率较传统方法提高了1.65倍。
The selection of the focusing window is the key procedure in achieving precise automatic focus of the microscope. For the traditional focus window selection method, the limitation is that the target object cannot be accurately positioned. This paper proposes an improved artificial fish focusing window method. The method takes the area-of-interest of the whole image as the basis of the selection window. Through utilizing the global optimization ability of the artificial fish swarm algorithm, the best focusing window can be obtained. Adding the global optimal value to the behavior update of each artificial fish makes the artificial fish quickly move to the optimal position. Under the premise of ensuring accuracy, the elimination behavior is introduced to improve the convergence speed of the algorithm in the later period. Furthermore, according to the characteristics of the bulletin board in the algorithm, the interference area is identified with the trend comparison method, and the influence of the non-target area is effectively excluded. Experiment results show that the focusing window obtained by this algorithm can be well-suited for the target object, greatly improve the accuracy of autofocus, and make the efficiency improvement 1.65 times than the traditional method.
The selection of the focusing window is the key procedure in achieving precise automatic focus of the microscope. For the traditional focus window selection method, the limitation is that the target object cannot be accurately positioned. This paper proposes an improved artificial fish focusing window method. The method takes the area-of-interest of the whole image as the basis of the selection window. Through utilizing the global optimization ability of the artificial fish swarm algorithm, the best focusing window can be obtained. Adding the global optimal value to the behavior update of each artificial fish makes the artificial fish quickly move to the optimal position. Under the premise of ensuring accuracy, the elimination behavior is introduced to improve the convergence speed of the algorithm in the later period. Furthermore, according to the characteristics of the bulletin board in the algorithm, the interference area is identified with the trend comparison method, and the influence of the non-target area is effectively excluded. Experiment results show that the focusing window obtained by this algorithm can be well-suited for the target object, greatly improve the accuracy of autofocus, and make the efficiency improvement 1.65 times than the traditional method.
引文
[1]Sun Y,Duthaler S,Nelson B J.Autofocusing in computer microscopy:Selecting the optimal focus algorithm[J].Microscopy Research&Technique,2004,65(3):139-149.
[2]Apolinar J,Rodríguez M.Three-dimensional microscope vision system based on micro laser line scanning and adaptive genetic algorithms[J].Optics Communications,2017,385:1-8.
[3]Jiang M S,Zhang N N,Zhang X D,et al.Applications of hybrid search strategy in microscope autofocus[J].Opto-Electronic Engineering,2017,44(7):685-694.江旻珊,张楠楠,张学典,等.混合搜索法在显微镜自动对焦中的应用[J].光电工程,2017,44(7):685-694.
[4]Li H G,Wang S,Sha X P,et al.Study of auto focusing technique of micro-vision system[J].Opto-Electronic Engineering,2014,41(8):1-9.李惠光,王帅,沙晓鹏,等.显微视觉系统中自动聚焦技术的研究[J].光电工程,2014,41(8):1-9.
[5]Jiang Z G,Han D B,Yuan T Y,et al.Study on auto focusing algorithm for automatic microscope[J].Journal of Image and Graphics,2004,9(4):396-401.姜志国,韩冬兵,袁天云,等.基于全自动控制显微镜的自动聚焦算法研究[J].中国图象图形学报,2004,9(4):396-401.
[6]Jiang T.Research on auto-focusing theory and technology based on image processing[D].Wuhan:Wuhan University of Technology,2008:10-12.蒋婷.基于图像处理的自动对焦理论和技术研究[D].武汉:武汉理工大学,2008:10-12.
[7]Li Q,Xu Z H,Feng H J,et al.Autofocus area design of digital imaging system[J].Acta Photonica Sinica,2002,31(1):63-66.李奇,徐之海,冯华君,等.数字成象系统自动对焦区域设计[J].光子学报,2002,31(1):63-66.
[8]Won C S,Pyun K,Gray R M.Automatic object segmentation in images with low depth of field[C]//Proceedings.International Conference on Image Processing,Rochester,NY,USA,2002,3:805-808.
[9]Fan P.Research on algorithm for auto-focus system based on digital image processing[D].Harbin:Harbin Institute of Technology,2009:20-28.樊攀.基于数字图像处理的自动聚焦系统算法研究[D].哈尔滨:哈尔滨工业大学,2009:20-28.
[10]Zhu K F,Jiang W,Gao Z,et al.Focusing window choice and parameters determination in automatic focusing system[J].Acta Optica Sinica,2006,26(6):836-840.朱孔凤,姜威,高赞,等.自动聚焦系统中聚焦窗口的选择及参量的确定[J].光学学报,2006,26(6):836-840.
[11]Li Q,Feng H J,Xu Z H.Autofocus system experiment study using variational image-sampling[J].Acta Photonica Sinica,2003,32(12):1499-1501.李奇,冯华君,徐之海.自动对焦系统中图像非均匀采样的实验研究[J].光子学报,2003,32(12):1499-1501.
[12]Wang Y F,Jiang W.Application of artificial fish swarm algorithm on adaptive auto-focusing window selection[J].Computer Engineering and Applications,2011,47(14):180-182.王彦芳,姜威.应用于聚焦窗口自适应选择的人工鱼群算法改进[J].计算机工程与应用,2011,47(14):180-182.
[13]Zhang X D,Wang h,Jiang M S,et al.Applications of saliency analysis in focus image fusion[J].Opto-Electronic Engineering,2017,44(4):435-441.张学典,汪泓,江旻珊,等.显著性分析在对焦图像融合方面的应用[J].光电工程,2017,44(4):435-441.
[14]Hu T,Chen S Z,Liu G D,et al.Algorithm of selecting the optimal focusing region[J].Optical Technique,2006,32(6):851-854.胡涛,陈世哲,刘国栋,等.图像法自动调焦的最佳调焦区域选取算法[J].光学技术,2006,32(6):851-854.
[15]Gu C C,Wu K J,Hu J,et al.Region sampling for robust and rapid autofocus in microscope[J].Microscopy Research&Technique,2015,78(5):382-390.
[16]Huang D T.Study on anto-focusing method using image techology[D].Changchun:Changchun Institute of Optics,Fine Mechanics and Physics Chinese Academy of Sciences,2013:76-78.黄德天.基于图像技术的自动调焦方法研究[D].长春:中国科学院长春光学精密机械与物理研究所,2013:76-78.
[17]Zhang F S,Li S W,Hu Z G,et al.Fish swarm window selection algorithm based on cell microscopic automatic focus[J].Cluster Computing,2017,20(1):485-495.
[18]Neshat M,Sepidnam G,Sargolzaei M,et al.Artificial fish swarm algorithm:a survey of the state-of-the-art,hybridization,combinatorial and indicative applications[J].Artificial Intelligence Review,2014,42(4):965-997.
[19]Yu L,Li C.A global artificial fish swarm algorithm for structural damage detection[J].Advances in Structural Engineering,2016,17(3):331-346.
[20]Groen F C A,Young I T,Ligthart G.A comparison of different focus functions for use in autofocus algorithms[J].Cytometry,1985,6(2):81-91.
[2]Apolinar J,Rodríguez M.Three-dimensional microscope vision system based on micro laser line scanning and adaptive genetic algorithms[J].Optics Communications,2017,385:1-8.
[3]Jiang M S,Zhang N N,Zhang X D,et al.Applications of hybrid search strategy in microscope autofocus[J].Opto-Electronic Engineering,2017,44(7):685-694.江旻珊,张楠楠,张学典,等.混合搜索法在显微镜自动对焦中的应用[J].光电工程,2017,44(7):685-694.
[4]Li H G,Wang S,Sha X P,et al.Study of auto focusing technique of micro-vision system[J].Opto-Electronic Engineering,2014,41(8):1-9.李惠光,王帅,沙晓鹏,等.显微视觉系统中自动聚焦技术的研究[J].光电工程,2014,41(8):1-9.
[5]Jiang Z G,Han D B,Yuan T Y,et al.Study on auto focusing algorithm for automatic microscope[J].Journal of Image and Graphics,2004,9(4):396-401.姜志国,韩冬兵,袁天云,等.基于全自动控制显微镜的自动聚焦算法研究[J].中国图象图形学报,2004,9(4):396-401.
[6]Jiang T.Research on auto-focusing theory and technology based on image processing[D].Wuhan:Wuhan University of Technology,2008:10-12.蒋婷.基于图像处理的自动对焦理论和技术研究[D].武汉:武汉理工大学,2008:10-12.
[7]Li Q,Xu Z H,Feng H J,et al.Autofocus area design of digital imaging system[J].Acta Photonica Sinica,2002,31(1):63-66.李奇,徐之海,冯华君,等.数字成象系统自动对焦区域设计[J].光子学报,2002,31(1):63-66.
[8]Won C S,Pyun K,Gray R M.Automatic object segmentation in images with low depth of field[C]//Proceedings.International Conference on Image Processing,Rochester,NY,USA,2002,3:805-808.
[9]Fan P.Research on algorithm for auto-focus system based on digital image processing[D].Harbin:Harbin Institute of Technology,2009:20-28.樊攀.基于数字图像处理的自动聚焦系统算法研究[D].哈尔滨:哈尔滨工业大学,2009:20-28.
[10]Zhu K F,Jiang W,Gao Z,et al.Focusing window choice and parameters determination in automatic focusing system[J].Acta Optica Sinica,2006,26(6):836-840.朱孔凤,姜威,高赞,等.自动聚焦系统中聚焦窗口的选择及参量的确定[J].光学学报,2006,26(6):836-840.
[11]Li Q,Feng H J,Xu Z H.Autofocus system experiment study using variational image-sampling[J].Acta Photonica Sinica,2003,32(12):1499-1501.李奇,冯华君,徐之海.自动对焦系统中图像非均匀采样的实验研究[J].光子学报,2003,32(12):1499-1501.
[12]Wang Y F,Jiang W.Application of artificial fish swarm algorithm on adaptive auto-focusing window selection[J].Computer Engineering and Applications,2011,47(14):180-182.王彦芳,姜威.应用于聚焦窗口自适应选择的人工鱼群算法改进[J].计算机工程与应用,2011,47(14):180-182.
[13]Zhang X D,Wang h,Jiang M S,et al.Applications of saliency analysis in focus image fusion[J].Opto-Electronic Engineering,2017,44(4):435-441.张学典,汪泓,江旻珊,等.显著性分析在对焦图像融合方面的应用[J].光电工程,2017,44(4):435-441.
[14]Hu T,Chen S Z,Liu G D,et al.Algorithm of selecting the optimal focusing region[J].Optical Technique,2006,32(6):851-854.胡涛,陈世哲,刘国栋,等.图像法自动调焦的最佳调焦区域选取算法[J].光学技术,2006,32(6):851-854.
[15]Gu C C,Wu K J,Hu J,et al.Region sampling for robust and rapid autofocus in microscope[J].Microscopy Research&Technique,2015,78(5):382-390.
[16]Huang D T.Study on anto-focusing method using image techology[D].Changchun:Changchun Institute of Optics,Fine Mechanics and Physics Chinese Academy of Sciences,2013:76-78.黄德天.基于图像技术的自动调焦方法研究[D].长春:中国科学院长春光学精密机械与物理研究所,2013:76-78.
[17]Zhang F S,Li S W,Hu Z G,et al.Fish swarm window selection algorithm based on cell microscopic automatic focus[J].Cluster Computing,2017,20(1):485-495.
[18]Neshat M,Sepidnam G,Sargolzaei M,et al.Artificial fish swarm algorithm:a survey of the state-of-the-art,hybridization,combinatorial and indicative applications[J].Artificial Intelligence Review,2014,42(4):965-997.
[19]Yu L,Li C.A global artificial fish swarm algorithm for structural damage detection[J].Advances in Structural Engineering,2016,17(3):331-346.
[20]Groen F C A,Young I T,Ligthart G.A comparison of different focus functions for use in autofocus algorithms[J].Cytometry,1985,6(2):81-91.