scholarly journals Analysis of time-resolved thermal responses in Lock-In thermography by independent component analysis (ICA) for a 3D-spatial separation of weak thermal sources and defects

Author(s):  
Michael Kögel ◽  
Sebastian Brand ◽  
Christian Große ◽  
Frank Altmann ◽  
Kristof J. P. Jacobs ◽  
...  

Abstract Lock-In Thermography is an established non-destructively operating method for the analysis of failures in microelectronic devices. In recent years a major improvement was achieved allowing the acquisition of the time-resolved temperature responses of weak thermal spots that enhances defect localization in 3D stacked semiconductor architectures. The assessment of a defect's depth based on the numerical estimation of the delay between excitation and thermal response by analyzing the value of the lock-in phase is often prone to thermal noise and parasitic effects. In sample structures that contain partial or full transparence for the infrared signal between the origin and the sample surface, the interference of the direct (radiated) and the conducted signal component largely falsifies the phase value on which the classical depth estimation relies. In the present study blind source separation based on independent component analysis of the thermal signals was successfully applied to separate interfering signal components arising from direct thermal radiation and conduction for a precise estimation of the defect depth.

2007 ◽  
Vol 25 (6) ◽  
pp. 860-868 ◽  
Author(s):  
Alain Smolders ◽  
Federico De Martino ◽  
Noël Staeren ◽  
Paul Scheunders ◽  
Jan Sijbers ◽  
...  

2020 ◽  
Vol 2020 (14) ◽  
pp. 357-1-357-6
Author(s):  
Luisa F. Polanía ◽  
Raja Bala ◽  
Ankur Purwar ◽  
Paul Matts ◽  
Martin Maltz

Human skin is made up of two primary chromophores: melanin, the pigment in the epidermis giving skin its color; and hemoglobin, the pigment in the red blood cells of the vascular network within the dermis. The relative concentrations of these chromophores provide a vital indicator for skin health and appearance. We present a technique to automatically estimate chromophore maps from RGB images of human faces captured with mobile devices such as smartphones. The ultimate goal is to provide a diagnostic aid for individuals to monitor and improve the quality of their facial skin. A previous method approaches the problem as one of blind source separation, and applies Independent Component Analysis (ICA) in camera RGB space to estimate the chromophores. We extend this technique in two important ways. First we observe that models for light transport in skin call for source separation to be performed in log spectral reflectance coordinates rather than in RGB. Thus we transform camera RGB to a spectral reflectance space prior to applying ICA. This process involves the use of a linear camera model and Principal Component Analysis to represent skin spectral reflectance as a lowdimensional manifold. The camera model requires knowledge of the incident illuminant, which we obtain via a novel technique that uses the human lip as a calibration object. Second, we address an inherent limitation with ICA that the ordering of the separated signals is random and ambiguous. We incorporate a domain-specific prior model for human chromophore spectra as a constraint in solving ICA. Results on a dataset of mobile camera images show high quality and unambiguous recovery of chromophores.


PIERS Online ◽  
2005 ◽  
Vol 1 (6) ◽  
pp. 750-753 ◽  
Author(s):  
Anxing Zhao ◽  
Yansheng Jiang ◽  
Wenbing Wang

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