The study of the light emitted by transistors in a highly scaled complementary metal oxide semiconductor (CMOS) integrated circuit (IC) has become a key method with which to analyze faulty devices, track the failure root cause, and have candidate locations for where to start the physical analysis. The localization of defective areas in IC corresponds to a reliability check and gives information to the designer to improve the IC design. The scaling of CMOS leads to an increase in the number of active nodes inside the acquisition area. There are also more differences between the spot’s intensities. In order to improve the identification of all of the photon emission spots, we introduce an unsupervised processing scheme. It is based on iterative thresholding decomposition (ITD) and mathematical morphology operations. It unveils all of the emission spots and removes most of the noise from the database thanks to a succession of image processing. The ITD approach based on five thresholding methods is tested on 15 photon emission databases (10 real cases and 5 simulated cases). The photon emission areas’ localization is compared to an expert identification and the estimation quality is quantified using the object consistency error.
In this article, a new implementation of active curves algorithms is proposed. It is question of an active region algorithm
based on stationary states of a nonlinear diffusion principle. Its originality is to obtain a set of geometric envelopes in
one pass, with a correspondence between level threshold of the grayscale result and a regularity scale, close to the
original shape. This set of geometric envelopes gives a multiscale representation, from a very regular approximation to a
full detailed and roughest representation. This property is used in a new subpixel circle center estimator developed in the
purpose of distorted contours. Results are very promising as precision is noticeably improved compared to a least mean
squares estimator. This estimator is then pretty well adapted to limit distortions caused by industrial processes.
The subject of this paper is the improvement of measures on imperfect circular forms. Indeed, simple geometric forms
have been well studied in image processing. Thus, articles describing circles on a discrete framework are numerous but
the case of imperfect geometric forms, in return, is hardly ever deepen. However, it is a classical problem in industrial
vision control process to not have a perfect, or perfectly discretized, geometric object due to, notably, manufacturing
process, industrial environment (dust, vibrations, objects displacement, etc.), interferences on acquisition chain
(electronic noise, lenses imperfections, etc. ). The authors present a comparison of measurement methods of circles
characteristics subpixel estimation (center's coordinates and radius) for several distortions (geometric or not). The
estimators proposed are classic least mean squares, 3D Hough algorithms and a method combining a Radon transform
based estimator and a FitzHugh-Nagumo partial differential equation based active region algorithm. The originality of
the method is to furnish a set of geometric envelopes in a single pass from a roughest to a full detailed representation.
Moreover, this multiple active region principle also offers interesting electronic implementation possibilities for real
time image processing for metrology on production chains.
This article deals with the problem of the determination of characteristics of imperfect circular objects on discrete images mainly the radius and center's coordinates. Imperfections are provided by discretization, noise and interior distortions present in some production processes. To this end, a multi-level method based on active contours was developed and tested on, noisy or not, misshaped or not, simulated circles whom centers and radius were known. The adequacy of this approach was tested with several methods, among them several Radon based ones. More particularly, this study indicates the relevance of the use of active contours combined with a Radon transform based method, using a description of circles from their tangents, improved thanks to a fitting considering the discrete implementation of Radon transform. Through this study, an active region algorithm based on stationary states of a non linear diffusion principle is proposed. Its originality is to obtain a set of geometric envelopes in one pass, with a correspondence between level threshold of the grayscale result and a regularity scale, more or less close to the original shape. This set of geometric envelopes gives a multiscale representation, from a very regular approximation to a full detailed and roughest representation. Then, a more robust measure of the circle parameters can be computed.
We consider an experimental setup, modelling the FitzHugh-Nagumo equation without recovery term and composed of a 1D nonlinear electrical network made up of discrete bistable cells, resistively coupled. In the first place, we study the propagation of topological fronts in the continuum limit, then in more discrete case. We propose to apply these results to the domain of signal processing. We show that erosion and dilation of a binary signal, can be obtained. Finally, we extend the study to 2D lattices and show that it can be of great interest in image processing techniques.