Autofocus in infrared microscopy

Raphael Abele 1, 2 Daniele Fronte 1 Pierre-Yvan Liardet 1 Jean-Marc Boi 2 Jean-Luc Damoiseaux 2 Djamal Merad 2
1 ST-ROUSSET - STMicroelectronics [Rousset]
2 LIS - Laboratoire d'Informatique et Systèmes
Abstract : Autofocus (AF) is a widely investigated subject in the fields of natural scene images, industrial assembly and biologic microscopy. This paper proposes a new effective AF method for infrared (IR) microscopy in the context of the Integrated Circuit industry (IC). The proposed method operates in the wavelet domain using a custom orthogonal wavelet for the 2D Discrete Wavelet Transform (DWT). The quality criterion of our AF algorithm relies on the standard deviance of the DWT coefficients, computed per subband and per level. Tested on several optical magnifying lenses, our method is robust time-efficient, and usable on-the-fly in the IC location system.
Keywords : Infrared imaging Microscopy Focusing Image analysis Image quality Image decomposition Wavelet transforms Statistics
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Conference papers
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Raphael Abele, Daniele Fronte, Pierre-Yvan Liardet, Jean-Marc Boi, Jean-Luc Damoiseaux, et al.. Autofocus in infrared microscopy. 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA), Sep 2018, Turin, France. pp.631-637, ⟨10.1109/ETFA.2018.8502648⟩. ⟨hal-02060828⟩

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