CONTENT-BASED AUTOFOCUSING IN AUTOMATED MICROSCOPY
CONTENT-BASED AUTOFOCUSING IN AUTOMATED MICROSCOPY
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DOI：
10.5566/ias.v29.p173-180
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发表时间：
2010-01-01
影响因子：
0.9
通讯作者：
Englmeier, Karl-Hans
中科院分区：
文献类型：
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作者：
Hamm, Peter;Schulz, Janina;Englmeier, Karl-Hans
自动对焦是使用自动显微镜设备进行图像采集和分析的基本步骤。尽管所有的努力，已经投入到开发一个可靠的自动对焦系统，最近的方法仍然缺乏鲁棒性对不同的显微镜模式和分散文物。本文提出了一种新的自动聚焦方法，通常适用于不同的显微镜模式（明场，相衬，微分干涉衬度（DIC）和荧光显微镜）。主要创新在于基于内容的焦点搜索，该搜索通过采用局部对象特征和增强学习来利用关于所观察对象的先验知识。因此，该方法背离了仅应用整个图像频率测量来获得焦平面的常见自动聚焦方法。因此，可以排除伪影，使其不被带入焦点计算以及定位特定微观物体的焦点对准层。
Autofocusing is the fundamental step when it comes to image acquisition and analysis with automated microscopy devices. Despite all efforts that have been put into developing a reliable autofocus system, recent methods still lack robustness towards different microscope modes and distracting artefacts. This paper presents a novel automated focusing approach that is generally applicable to different microscope modes (bright-field, phase contrast, Differential Interference Contrast (DIC) and fluorescence microscopy). The main innovation consists in a Content-based focus search that makes use of a priori knowledge about the observed objects by employing local object features and Boosted Learning. Hence, this method turns away from common autofocus approaches that apply solely whole image frequency measurements to obtain the focus plane. Thus, it is possible to exclude artefacts from being brought into focus calculation as well as locating the in-focus layer of specific microscopic objects.