METHOD FOR EXTRACTING NON-PERIODICAL PATTERNS MASKED BY PERIODICAL PATTERNS, AND DEVICE IMPLEMENTING THE METHOD

Abstract

A method is provided for extracting information of interest from a measurement signal having a periodic interference pattern, which includes steps (i) of generating a filtering function representing the frequency components of the interference pattern, by implementing an analysis of an amplitude spectrum of the measurement signal based on morphological criteria, (ii) of applying the filtering function to the measurement signal so as to generate an interference signal constituted essentially by the interference pattern, and (iii) of calculating a filtered signal by carrying out a difference between the measurement signal and the interference signal.

The invention also relates to a device implementing the method.

Claims

1. A method for extracting information of interest from a measurement signal comprising a periodic interference pattern, comprising steps of: generating a filtering function representative of the frequency components of the interference pattern, by implementing an analysis of an amplitude spectrum of the measurement signal based on morphological criteria; applying said filtering function to the measurement signal so as to generate an interference signal constituted essentially by the interference pattern; and calculating a filtered signal by carrying out a difference between the measurement signal and the interference signal.

2. The method according to claim 1, which comprises a step of generating the amplitude spectrum of the measurement signal with application of a dynamic range compression to the amplitude of the frequency spectrum of said measurement signal.

3. The method according to claim 1, which comprises a step of multiplying the frequency spectrum of the measurement signal by the filtering function.

4. The method according to claim 1, which comprises a step of searching, in the amplitude spectrum of the measurement signal, for zones known as h-maxima zones corresponding respectively to sets of related points around local amplitude maximas satisfying a minimum height criterion with respect to the closest local amplitude minimas.

5. The method according to claim 4, in which the minimum height criterion is defined as a predetermined fraction of the maximum amplitude of the amplitude spectrum of the measurement signal.

6. The method according to claim 4, which comprises steps of: generating a shifted amplitude spectrum corresponding to the amplitude spectrum of the measurement signal shifted towards the lower amplitudes by a quantity corresponding to the minimum height criterion and bounded at zero; geodesic reconstruction of said shifted amplitude spectrum in the amplitude spectrum of the measurement signal, so as to obtain a clipped amplitude spectrum corresponding to the amplitude spectrum of the measurement signal clipped of the quantity corresponding to the minimum height criterion in the h-maxima zones; and calculating an amplitude spectrum of the h-maxima zones by difference between the amplitude spectrum of the measurement signal and the clipped amplitude spectrum.

7. The method according to claim 4, which comprises a step of generating a filtering function with zero values outside the h-maxima zones, and a constant non-zero value in said h-maxima zones.

8. The method according to claim 1, which comprises steps of: localizing the local minimas of the amplitude spectrum of the measurement signal; geodesic reconstruction of said local minimas in the amplitude spectrum of the measurement signal so as to obtain a base amplitude spectrum representative of the amplitude at the base of the peaks of the amplitude spectrum of the measurement signal; and calculating an amplitude spectrum of the peaks by difference between the amplitude spectrum of the measurement signal and the base amplitude spectrum.

9. The method according to claim 8, which comprises a step of generating a filtering function from the amplitude spectrum of the peaks, with a constant non-zero value in the zones of the amplitude spectrum of the peaks with an amplitude above a predetermined binarization threshold, and a zero value elsewhere.

10. The method according to claim 1, which also comprises a step of filling shallow local minimas with: a generation of an inverted amplitude spectrum corresponding to an amplitude symmetry of the amplitude spectrum of the measurement signal; a generation of an inverted and shifted amplitude spectrum, by shifting said inverted amplitude spectrum towards the low amplitudes by a quantity representing a depth of minimas to be filled, and a geodesic reconstruction of said inverted and shifted amplitude spectrum in said inverted amplitude spectrum.

11. The method according to claim 1, which comprises steps of: generating a reference filtering function representative of the frequency components of the interference pattern, by implementing an analysis of an amplitude spectrum of a reference signal comprising essentially the reference pattern; identifying maximas of the amplitude spectrum of the measurement signal; and generating a filtering function by adjustment of the reference filtering function over the identified maximas of the amplitude spectrum of the measurement signal.

12. The method according to claim 1, which is implemented with a measurement signal comprising an image of one of the following types: image of at least one part of a wafer, image of at least one part of an assembly of wafers, image of at least one part of a wafer fixed on a wafer carrier.

13. The method according to claim 12, which comprises a step of extracting information of interest of one of the following forms: identification information, alphanumeric characters, written signs, 1D barcode, 2D barcode, QR code.

14. A method for extracting identification information of a wafer at least partially masked by a wafer carrier with a structure of periodic holes, comprising steps of: acquiring an image comprising the identification information; and extracting said identification information by implementing the steps of the method according to claim 1.

15. A device for extracting information of interest from a measurement signal comprising a periodic interference pattern comprising: imaging means for acquiring a measurement signal in the form of an image, and calculation means arranged to: generate a filtering function representing the frequency components of the interference pattern, by implementing an analysis of an amplitude spectrum of the measurement signal based on morphological criteria; apply said filtering function to the measurement signal so as to generate an interference signal constituted essentially by the interference pattern; and calculate a filtered signal by carrying out a difference between the measurement signal and the interference signal.

Description

DESCRIPTION OF THE FIGURES AND EMBODIMENTS

[0084] Other advantages and characteristics of the invention will become apparent on reading the detailed description of implementations and embodiments which are in no way limitative, and from the following attached drawings:

[0085] FIG. 1 illustrates an embodiment of the method according to the invention for identifying references of wafers bonded to perforated carriers,

[0086] FIG. 2 illustrates a general block diagram of the method according to the invention,

[0087] FIG. 3 illustrates the generation of the filtering function according to a first embodiment of the invention,

[0088] FIG. 4 illustrates the generation of the filtering function according to a second embodiment of the invention,

[0089] FIG. 5 illustrates a variant that can be applied to the first and second embodiments of the invention,

[0090] FIG. 6 illustrates results obtained with the method according to the invention, a first initial image in FIG. 6a, the corresponding filtered image in FIG. 6b, a second initial image in FIG. 6c and the corresponding filtered image in FIG. 6d.

[0091] It is well understood that the embodiments that will be described hereinafter are in no way limitative. Variants of the invention can in particular be envisaged comprising only a selection of the characteristics or steps described below in isolation from the other described characteristics or steps, if this selection of characteristics or steps is sufficient to confer a technical advantage or to differentiate the invention with respect to the state of the prior art.

[0092] In particular, all the described variants and embodiments can be combined if there is no objection to this combination from a technical point of view.

[0093] In the figures, the components common to several figures retain the same references.

[0094] With reference to FIG. 1, an embodiment of the invention in a microelectronics process will be described, for reading or identifying identification codes on wafers intended to be used for the production of integrated circuits.

[0095] These wafers 10 are provided with an identification code 11, in particular with the aim of traceability during the steps of the process. In the example presented, this identification code 11 comprises alphanumeric characters.

[0096] In order to perform thinning operations in particular, the wafers 10 are bonded to glass carriers 12. These carriers 12 are perforated in the form of a periodic pattern 13 of perforations. In this case, the identification pattern 11 present on the wafer 10 under the carrier 12 (or optionally on the carrier 12 itself) is only partially apparent because of the presence of the periodic pattern 13 of perforations. This identification pattern 11 is therefore partially masked by the carrier 12, either because it is partially covered by the carrier 12 or because it is only partially printed or etched on the carrier 12 in its filled zones.

[0097] In order to identify a wafer 10, an imaging device can be used which comprises a camera 14 (or any other imaging means) and calculation means 15 for example based on a microprocessor or a computer: [0098] an image of the identification pattern 11 is acquired with the camera 14; [0099] a processing of the image is performed in order to extract the identification pattern 11 from it (segmentation); [0100] the information of the identification pattern 11 is extracted in order to obtain the identifier 16 of the wafer 10, for example by means of character recognition (OCR) software or barcode reader software, as appropriate.

[0101] In this case, in order to be able to read the identification pattern 11 and, for example, to recognize its characters using OCR, it is necessary to process the image taken by the camera 14 in order to filter out the periodic pattern 13 and essentially leave only the elements of the identification pattern 11 (the characters) visible.

[0102] The subject of the method according to the invention is precisely this. In the embodiment presented, it is implemented in calculation means 15 arranged for this purpose.

[0103] With reference to FIG. 2, the method according to the invention therefore comprises a step 21 of acquiring or obtaining a measurement signal in the form of an initial image I, which comprises information of interest 11 (the identification code 11) partially masked by a periodic interference pattern 13 (the periodic pattern 13).

[0104] The initial image I can be acquired directly by the camera 14, or originate from a storage means (hard disk, memory, etc.).

[0105] Non-limitatively, an initial image I in which the identification code 11 appears dark on a light background, and where the periodic pattern 13 which has the form of a periodic matrix of holes 13 is also dark, is considered in the embodiment presented. The level of intensity of the holes of the periodic pattern 13 can be equivalent to that of the fragments of characters of the identification code 13, which prevents any spatial segmentation by greyscale according to known methods.

[0106] It is to be noted that in the case of an initial image I with a white identification pattern or white characters 11 on a black background it is sufficient to take a negative of this initial image I at the start in order to be in the configuration described previously.

[0107] An apodized image I.sub.a is then constructed, which corresponds to the initial image I in which the intensity of the pixels on a margin with width A is reduced in order to tend towards a constant value (for example 0) at the edge of the image. The apodization function can be, for example, a Gaussian function, or more simply a linear decrease. The apodized image I.sub.a is obtained by multiplying the initial image I by the apodization function.

[0108] The benefit of this apodization step (which, however, is not essential) is to limit the edge effects during the calculation of the Fourier transform: as the digital Fourier transform assumes a periodic image, any discontinuity between the left-hand and right-hand edges (and top and bottom) of the image leads to the appearance of virtual frequencies due to an aliasing effect. It is therefore preferable to use an apodization function which has a spectrum limited essentially to low frequencies.

[0109] The method according to the invention also comprises a step 22 of calculating the frequency spectrum F of the initial image I. This frequency spectrum F is obtained by means of a two-dimensional digital Fourier transform calculation.

[0110] As the initial image I is in effective values, the frequency spectrum F is therefore a complex image with Hermitian symmetry.

[0111] The method according to the invention then comprises a step 23 of calculating an amplitude spectrum F.sub.m of the initial image I. In the embodiment presented, this amplitude spectrum F.sub.m corresponds to the logarithm of the norm or of the modulus of the frequency spectrum F:

F.sub.m=log(abs(F)).

[0112] The benefit of taking the logarithm of the modulus of the frequency spectrum F and not simply its modulus is that this introduces a compression of the dynamic range of the amplitude spectrum F.sub.m. In general, the spectral intensity in the frequency spectrum F around the zero frequency is several orders of magnitude above that of the high frequencies: the logarithmic compression makes it possible to further reduce the extent of the dynamic range.

[0113] The method according to the invention also comprises a step 24 of generating a filtering function representative of the frequency components of the periodic interference pattern 13.

[0114] This filtering function is obtained by implementing an analysis of the amplitude spectrum F.sub.m on the basis of morphological criteria. Several variants of this analysis are possible within the framework of the invention. They will be described below.

[0115] In general: [0116] the peaks of the amplitude spectrum F.sub.m which correspond to the characteristic frequencies of the periodic pattern 13 are selected by implementing morphological criteria and/or methods originating from mathematical morphology; and [0117] a binary mask B which precisely represents the selection in the amplitude spectrum F.sub.m of the frequency peaks corresponding to the characteristic frequencies of the periodic pattern 13 is created.

[0118] This binary mask comprises non-zero values (for example one) for the frequencies corresponding to the zones of the selected frequency peaks and zero values (zero) for the other frequencies.

[0119] The method according to the invention also comprises a step 25 of masking the frequency spectrum F with the binary mask B in order to generate a filtered frequency spectrum F.sub.B. This masking can be carried out for example by an operation multiplying the frequency spectrum F by the binary mask B:

F.sub.B=FB.

[0120] Thus, any complex element of F which does not belong to B is set to zero in F.sub.B, and otherwise is retained.

[0121] This masking operation is carried out so as to retain the Hermitian symmetry of the frequency spectrum F in the filtered frequency spectrum F.sub.B.

[0122] To this end, it is possible, for example: [0123] to generate an even mask B, i.e. which has one and the same value for each frequency and for the corresponding frequency with the opposite sign; [0124] or, more generally, to generate a mask B corresponding to the part of the spectral plane in which the FFT is calculated.

[0125] The method according to the invention also comprises a step 26 of calculating the two-dimensional inverse Fourier transform of the filtered frequency spectrum F.sub.B. An image known as the interference image J is thus obtained which is real if the Hermitian symmetry of the frequency spectrum F was respected during the masking.

[0126] The interference image J corresponds to the initial image I (or more precisely the apodized initial image I.sub.a) filtered of all the elements of I that are non-periodic (or have low spectral energy). The interference image J therefore comprises essentially the periodic interference pattern 13. This interference image J also retains the variations in illumination of the initial image I because the very low frequencies belong to the peak the vertex of which is the zero frequency.

[0127] The method according to the invention also comprises a step 27 of calculating a filtered image R, corresponding to a pixel-by-pixel difference between the interference image J and the initial image I (or more precisely the apodized initial image I.sub.a):

R=JI.sub.a.

[0128] In this filtered image R, the non-periodic elements of the initial image I appear with a high intensity, the rest being dark. The negative intensities are thresholded to zero. They appear in particular because pixels of the interference image J can be negative. This is explained by the fact that the energy of the initial image I is retained while certain frequencies are suppressed, creating a larger dynamic range.

[0129] Thus, in the filtered image R, the fragments of characters 11 appear clear and brilliant, or at least in a clearly more discernible manner than in the measurement image I.

[0130] Known segmentation and character recognition (OCR) techniques can then be implemented much more effectively in order to extract the information of the identification pattern 11 and obtain the identifier 16 of the wafer 10.

[0131] With reference to FIG. 3, a first method of generating the binary mask B will now be described in detail.

[0132] For reasons of clarity, this method of generating the binary mask B is illustrated by one-dimensional curves. Such curves can be, for example, representative of a profile along a frequency axis of the amplitude spectrum F.sub.m.

[0133] It is to be noted that they can also be illustrative of an implementation of the method according to the invention on a one-dimensional measurement signal.

[0134] Of course, the operations which are described below can be applied both to one-dimensional measurement signals and to two-dimensional images.

[0135] Firstly, the zones 34 known as h-maxima zones are sought in the amplitude spectrum F.sub.m (curve 30). These zones 34, also called h-maxima according to the terminology of mathematical morphology, correspond respectively to sets of related points around local amplitude maximas 33 which satisfy a minimum height criterion h with respect to the closest local amplitude minimas.

[0136] Preferably, the minimum height criterion h is defined as being a fraction of the maximum amplitude of the amplitude spectrum F.sub.m. For example, h can be set at 25% of this maximum amplitude.

[0137] In order to determine these h-maxima zones, a shifted amplitude spectrum F.sub.d (curve 31) is generated which corresponds to the amplitude spectrum F.sub.m shifted in terms of amplitude, towards the lower amplitudes, by h:

F.sub.d=F.sub.mh.

[0138] A clipped amplitude spectrum F.sub.e is then calculated by performing a geodesic reconstruction of the shifted amplitude spectrum F.sub.d in the amplitude spectrum F.sub.m.

[0139] This geodesic reconstruction is defined as a repetition until the amplitude spectrum F.sub.m of a dilation of the shifted amplitude spectrum F.sub.d with a plane structuring element g parallel to the plane of the frequencies (or one-dimensional parallel to the axis of the frequencies in the case of one-dimensional geodesic reconstruction) is reached.

[0140] Mathematically, this geodesic reconstruction can be written as follows:

E.sub.g.sup.Fm(F.sub.d)=sup.sub.n0{(.sub.g.sup.Fm).sup.n(F.sub.d)},

[0141] where the index n indicates an iteration and .sub.g.sup.Fm(F.sub.d) is the geodesic dilation of F.sub.d in F.sub.m with the structuring element g. Then:

.sub.g.sup.Fm(F.sub.d)=.sub.g(F.sub.d)F.sub.m,

[0142] where .sub.9(F.sub.d) is the dilation of F.sub.d by the structuring element g and the operator (inf) returns the minorant or the largest of the minorants.

[0143] Graphically, the result of the geodesic reconstruction of the shifted amplitude spectrum F.sub.d in the amplitude spectrum F.sub.m (corresponding to the clipped amplitude spectrum F.sub.e) is illustrated by the curve 32. This clipped amplitude spectrum F.sub.e curve therefore corresponds to the amplitude spectrum F.sub.m clipped of the h-maxima zones 34 (i.e. clipped at amplitudes lower of h than the amplitude of the local maximas 33 which satisfy the criterion of the h-maximas).

[0144] An amplitude spectrum of the h-maxima zones F.sub.mh is then calculated by carrying out the difference between the amplitude spectrum F.sub.m and the clipped amplitude spectrum F.sub.e corresponding to the geodesic reconstruction

E.sub.g.sup.Fm(F.sub.d).

[0145] Then, the amplitude spectrum of the h-maxima zones F.sub.mh is binarized with respect to a predefined binarization threshold.

[0146] A mask B with non-zero values (for example one) in the zones 35 above the binarization threshold and zero values in the zones below the binarization threshold is thus obtained. If this binarization threshold is set at zero, as illustrated in FIG. 3, the non-zero zones 35 of the mask B correspond to the h-maximas 34.

[0147] In this way, a mask B that is very representative of the spectral zones in which the energy due to the periodic pattern 13 is significant is obtained. It is thus possible to take account not only of the position of the frequency peaks but also of their width or their extent. This makes it possible to reconstruct the periodic pattern 13 very accurately and very faithfully.

[0148] With reference to FIG. 4, a second method of generating the binary mask B will now be described in detail.

[0149] As before, for reasons of clarity, this method of generating the binary mask B is illustrated by one-dimensional curves. Such curves can be, for example, representative of a profile along a frequency axis of the amplitude spectrum F.sub.m.

[0150] It is to be noted that they can also be illustrative of an implementation of the method according to the invention on a one-dimensional measurement signal.

[0151] Of course, the operations which are described below can be applied both to one-dimensional measurement signals and to two-dimensional images.

[0152] Firstly, the local minimas 41 are sought in the amplitude spectrum F.sub.m (curve 30).

[0153] A spectrum of the minimas F.sub.min (curve 42) is thus defined which has the value of the local minimas 41 at the corresponding frequencies and a zero value at the other frequencies.

[0154] A base amplitude spectrum F.sub.b is then calculated by performing a geodesic reconstruction of the spectrum of the minimas F.sub.min in the amplitude spectrum F.sub.m.

[0155] As before, the geodesic reconstruction is defined as a repetition until the amplitude spectrum F.sub.m of a dilation of the spectrum of the minimas F.sub.min with a plane structuring element g parallel to the plane of the frequencies (or one-dimensional parallel to the axis of the frequencies in the case of one-dimensional geodesic reconstruction) is reached.

[0156] Mathematically, this geodesic reconstruction can be written as follows:

E.sub.g.sup.Fm(F.sub.min)=sup.sub.n0{(.sub.g.sup.Fm).sup.n(F.sub.min)},

where the index n indicates an iteration and .sub.g.sup.Fm(F.sub.min) is the geodesic dilation of F.sub.min in F.sub.m with the structuring element g. Then:

.sub.g.sup.Fm(F.sub.min)=.sub.g(F.sub.min)F.sub.m,

[0157] where .sub.g(F.sub.min) is the dilation of F.sub.d by the structuring element g and the operator (inf) returns the largest of the minorants.

[0158] Graphically, the result of the geodesic reconstruction of the spectrum of the minimas F.sub.min in the amplitude spectrum F.sub.m (corresponding to the base amplitude spectrum F.sub.b) is illustrated by the curve 43. This base amplitude spectrum F.sub.b is thus representative of the continuous background of the amplitude spectrum F.sub.m.

[0159] An amplitude spectrum of the peaks F.sub.p is then calculated by difference between the amplitude spectrum F.sub.m and the base amplitude spectrum F.sub.b. This amplitude spectrum of the peaks F.sub.p is illustrated by the curve 44.

[0160] Then, the amplitude spectrum of the peaks F.sub.p is binarized with respect to a binarization threshold h.sub.p. This binarization threshold h.sub.p can, for example, be set as a fraction of the maximum amplitude of the amplitude spectrum of the peaks F.sub.p. In the embodiment illustrated in FIG. 4, this binarization threshold h.sub.p is set at 50% of the maximum amplitude of the amplitude spectrum of the peaks F.sub.p, so as to reject the low amplitude peaks.

[0161] A mask B with non-zero values (for example one) in the zones 35 above the binarization threshold h.sub.p and zero values in the zones below the binarization threshold is thus obtained.

[0162] In this way, a mask B that is very representative of the spectral zones in which the energy due to the periodic pattern 13 is significant is obtained. It is thus possible to take account not only of the position of the frequency peaks but also of their width or their range. This makes it possible to reconstruct the periodic pattern 13 very accurately and very faithfully.

[0163] With reference to FIG. 5, according to a variant, the method according to the invention can comprise an additional step of filling of the shallow local minimas of the amplitude spectrum F.sub.m. This step can be implemented with the first method or with the second method of generating the binary mask B.

[0164] The objective of this variant is to eliminate the artifacts which can appear when the amplitude spectrum F.sub.m comprises very close, partially merged peaks.

[0165] According to this variant, the binary mask B is generated according to the methods described with reference to FIG. 3 and FIG. 4 from a filled amplitude spectrum F.sub.mc instead of using the amplitude spectrum F.sub.m.

[0166] The filled amplitude spectrum F.sub.mc is calculated as follows: [0167] an inverted amplitude spectrum F.sub.mi (curve 51) corresponding to an amplitude symmetry of the amplitude spectrum F.sub.m (curve 30) is generated; [0168] then an inverted and shifted amplitude spectrum F.sub.mid is generated by shifting the inverted amplitude spectrum F.sub.mi towards the low amplitudes by a quantity h.sub.e representing the depth of minimas to be filled; [0169] then a filled inverted amplitude spectrum F.sub.mci (curve 53) is calculated by performing a geodesic reconstruction of the inverted and shifted amplitude spectrum F.sub.mid in the inverted amplitude spectrum F.sub.mi:

F.sub.mci=E.sub.g.sup.Fmi(F.sub.fmid)=sup.sub.n0{(.sub.g.sup.Fmi).sup.n(F.sub.mid)}; [0170] finally, the filled amplitude spectrum F.sub.mc (curve 54) is obtained by performing an amplitude symmetry on the inverted filled amplitude spectrum F.sub.mci.

[0171] As illustrated in FIG. 5, the thus-obtained filled amplitude spectrum F.sub.mc corresponds to the amplitude spectrum F.sub.m in which the minimas with a depth up to the quantity h.sub.e (or, in other words, the h-minimas with a depth parameter between 0 and h.sub.c) are filled. It is to be noted that the h-minimas with a depth greater than h.sub.e are not affected.

[0172] A third method of generating the binary mask B will now be described in detail.

[0173] In this embodiment, a predetermined reference filtering function, in the form of a reference mask B.sub.r, is used.

[0174] This reference mask B.sub.r is a binary mask representing the frequency components of the periodic interference pattern 13. It is determined from a reference image.

[0175] This reference image can be obtained in different ways. It can be, for example: [0176] a theoretical image, generated from a modelling of the periodic pattern 13; [0177] an image obtained by imaging, with a camera, a zone in which there is essentially only the periodic pattern 13.

[0178] The reference binary mask B.sub.r is therefore generated from the reference image. To this end, one of the methods described previously with reference to FIG. 3, FIG. 4 and FIG. 5 can preferably be used.

[0179] In this way, a reference binary mask B.sub.r that is very representative of the spectral zones in which the energy due to the periodic pattern 13 is significant is obtained, which takes account not only of the position of the frequency peaks but also of their width or their range.

[0180] A reference binary mask B.sub.r can thus be calculated once and for all.

[0181] The use of the reference mask B.sub.r to extract information of interest 11 that is partially masked by a periodic interference pattern 13 of an initial image I will now be described.

[0182] It is assumed, of course, that the periodic pattern 13 of the image I is similar to that which was used to generate the reference mask B.sub.r.

[0183] The imaging conditions for this periodic pattern 13 can be different between the reference image and the initial image I. In this case, at least initially (without deformations of the imaged surface), these differences in imaging conditions can be modelled essentially by at least one of the following transformations: a translation, a rotation and a magnification or a homothety.

[0184] In this embodiment of the invention, as before, the initial image I can be acquired directly by the camera 14, or originate from a storage means (hard disk, memory, etc.).

[0185] It is then processed according to the general method described previously with reference to FIG. 1.

[0186] In order to generate the binary mask B: [0187] an amplitude spectrum F.sub.m is calculated as before, [0188] the main local maximas of this amplitude spectrum F.sub.m are detected. This detection can be performed with a simple algorithm since it is possible to limit it to the detection of the position of the most significant frequency peaks (essentially due to the periodic pattern 13). [0189] an adjustment in the frequency domain of the reference binary mask B.sub.r is then performed in order that it is best adapted or corresponds best to the main local maximas of the amplitude spectrum F.sub.m. Advantageously, this adjustment can be performed with a limited set of transformations since it is possible to limit it to the transformations which relate to the modulus of the Fourier transform: homotheties along the frequency axis or axes with the zero frequency for origin and/or rotation about the zero frequency. In particular, it is not necessary to take account of the spatial translations of the initial image I which only affect the phase of the Fourier transform.

[0190] A deformed version T(B.sub.r) of the reference binary mask B.sub.r which corresponds to the sought binary mask B is thus obtained:

B=T(B.sub.r).

[0191] The transformation function T comprises a transformation or a combination of transformations from: one or more homotheties along the frequency axis or axes with the zero frequency for origin and/or a rotation about the zero frequency.

[0192] The adjustment can be performed according to known methods, for example by minimizing an error function in the least-squares sense.

[0193] FIG. 6 illustrates results obtained with the method according to the invention. The presented images are details of processed images.

[0194] FIG. 6a and FIG. 6c show initial images I obtained with a camera 14 on wafers 10 bonded to glass carriers 12, perforated in the form of a periodic pattern 13 of perforations. As can be seen, the identification pattern 11 present (an alphanumeric inscription) is difficult to read on these images, in particular on that of FIG. 6c.

[0195] FIG. 6b and FIG. 6d show filtered images R obtained with the method according to the invention in the embodiment thereof described with reference to FIG. 3, and applied respectively to the initial images I of FIG. 6a and FIG. 6c.

[0196] In FIG. 6d, an anisotropic filtering has also been applied.

[0197] As can be seen, in particular in FIG. 6d, the method according to the invention greatly improves the readability of the identification pattern 11, both for the human eye and for processing with a character recognition (OCR) algorithm.

[0198] Of course, the invention is not limited to the examples which have just been described and numerous adjustments can be made to these examples without exceeding the scope of the invention.