FMPOD: A Novel Focus Metric Based on Polynomial Decomposition for Infrared Microscopy

Abele, Raphael; Moubtahij, Redouane El; Fronte, Daniele; Liardet, Pierre-Yvan; Damoiseaux, Jean-Luc; Boï, Jean-Marc; Merad, Djamal

doi:10.1109/jphot.2019.2940689

Cited by 3 publications

(3 citation statements)

References 39 publications

(44 reference statements)

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“…To deal with these specific constraints, an AF was proposed in [ 30 ] based on special IC viewing features, analyzed in the time-frequency domain. The Focus Metric based on POlynomial Decomposition (FMPOD) is proposed to evaluate the focus level of images acquired for a varying distance of the optical system from the SOI.…”

Section: Scanning System For Viewing Integrated Circuitsmentioning

confidence: 99%

“…In [ 30 ], the use of a Legendre polynomial for the FMPOD is justified by its ability to raise features of interest in infrared images of IC. The authors propose a focus metric by analyzing the directional features highlighted through polynomial decomposition, features considered as relevant to describe a focused image.…”

Section: Scanning System For Viewing Integrated Circuitsmentioning

confidence: 99%

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Spatial Location in Integrated Circuits through Infrared Microscopy

Abele

Damoiseaux

Moubtahij

et al. 2021

Sensors

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In this paper, we present an infrared microscopy based approach for structures’ location in integrated circuits, to automate their secure characterization. The use of an infrared sensor is the key device for internal integrated circuit inspection. Two main issues are addressed. The first concerns the scan of integrated circuits using a motorized optical system composed of an infrared uncooled camera combined with an optical microscope. An automated system is required to focus the conductive tracks under the silicon layer. It is solved by an autofocus system analyzing the infrared images through a discrete polynomial image transform which allows an accurate features detection to build a focus metric robust against specific image degradation inherent to the acquisition context. The second issue concerns the location of structures to be characterized on the conductive tracks. Dealing with a large amount of redundancy and noise, a graph-matching method is presented—discriminating graph labels are developed to overcome the redundancy, while a flexible assignment optimizer solves the inexact matching arising from noises on graphs. The resulting automated location system brings reproducibility for secure characterization of integrated systems, besides accuracy and time speed increase.

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Section: Scanning System For Viewing Integrated Circuitsmentioning

confidence: 99%

Section: Scanning System For Viewing Integrated Circuitsmentioning

confidence: 99%

Spatial Location in Integrated Circuits through Infrared Microscopy

Abele

Damoiseaux

Moubtahij

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…These approaches can be categorized into the following groups based on the principles applied. 1) Analyzing images acquired using software algorithm to determine the best focus [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]; 2) based on auxiliary laser focusing spot deviation or spot diameter variation [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Study of Microscope Autofocus Based on Weighted Light Intensity

Lu¹,

Tu²,

Wu³

et al. 2021

AJPA

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Microscopes auto focusing is critically important for a great spectrum of scientific and industrial applications.Finding the best focus position for variety of surfaces under measurement proved to be challenging. In order to provide a rapid and accurate method for microscope focusing positioning, a laser focus deviate system was employed for microscope focusing position. The relationship between focusing sensitivity and the surface under measurement was investigated. First, the laser focus deviate technique is introduced in light of characteristic parameters such as the diameter of the focused spot, the laser wavelength and the distance from the optimal focus. Then, the focusing displacement versus spot position curve fitting is performed for a smooth isotropic surface to directly locate the best focusing position. Following, it is analyzed that when applied to anisotropic and rough surfaces, the centroid of the image spot after reflection/scattering from the surface will deviate from its original light intensity distribution, thus deviate from the calculated optimal focus position and cause focusing errors. Finally, a criterion of weighted light intensity value Q is introduced to achieve fast focusing of anisotropic surfaces in combination with the laser focusing deviate technique. The experimental results show that for a 20× microscope objective system, the focusing accuracy of this focusing positioning method is 1.7 µm on smooth surfaces; and is at the micro meter level for rough surfaces. It basically meets the requirements for rapid, stable and reliable microscope auto focusing needs.

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