Abstract: A method of non-destructive checking of a component for aeronautics, the method including the following steps of acquiring a volume by tomographic imaging, of generating by computer simulation a surface corresponding to the component to be analyzed, of registering the volume and the surface by optimizing a similarity criterion defined by a function taking into account the correlation between normal vectors of a field of normal vectors of the surface displaced by transformation and a gradient of a gradient field of the volume, the optimization being performed as a function of transformations for determining the optimal transformation which maximizes the similarity criterion, of storing the optimal transformation, of establishing the correspondence between the surface and the volume obtained with the aid of the optimal transformation.

Abstract: A method for the non-destructive examination of aeronautical parts utilizing a system for acquiring x-ray images of the aeronautical parts, the method including verifying the system for acquiring x-ray images of the aeronautical parts, the verification including the steps of: acquiring an x-ray image of a known reference part including predefined structures, recognizing the predefined structures of the known reference part in the acquired x-ray image, measuring image quality on the basis of the result of the recognition step, wherein the recognition of the predefined structures of the known reference part in the acquired x-ray image includes the steps of: using information extracted from the acquired image in order to produce first structure information, and combining the first structure information with information representing a priori knowledge of the structures, by modelling using a Markov chain, in order to produce second structure information.

Abstract: A method for the non-destructive examination of aeronautical parts utilizing a system for acquiring x-ray images of the aeronautical parts, the method including verifying the system for acquiring x-ray images of the aeronautical parts, the verification including the steps of: acquiring an x-ray image of a known reference part including predefined structures, recognizing the predefined structures of the known reference part in the acquired x-ray image, measuring image quality on the basis of the result of the recognition step, wherein the recognition of the predefined structures of the known reference part in the acquired x-ray image includes the steps of: using information extracted from the acquired image in order to produce first structure information, and combining the first structure information with information representing a priori knowledge of the structures, by modelling using a Markov chain, in order to produce second structure information.

Abstract: The method of estimating a quality index of a gray-scale encoded three-dimensional image of a composite material part includes an obtaining step for obtaining a histogram from the image, the histogram representing for each class of a plurality of classes each including at least one gray-scale level, the number of voxels of the image having a gray-scale level belonging to the class; an extraction step for extracting a predetermined number of Gaussian functions present in the histogram; and an estimation step for estimating at least one quality index of the image from parameters characterizing the Gaussian functions extracted from the histogram.

Abstract: A method of non-destructive checking of a component for aeronautics, the method including the following steps of acquiring a volume by tomographic imaging, of generating by computer simulation a surface corresponding to the component to be analyzed, of registering the volume and the surface by optimizing a similarity criterion defined by a function taking into account the correlation between normal vectors of a field of normal vectors of the surface displaced by transformation and a gradient of a gradient field of the volume, the optimization being performed as a function of transformations for determining the optimal transformation which maximizes the similarity criterion, of storing the optimal transformation, of establishing the correspondence between the surface and the volume obtained with the aid of the optimal transformation.

Abstract: A method of characterizing a part made of woven composite material, includes calculating autocorrelation values of a three-dimensional image in an observation window of the volume of the part for a plurality of spatial vectors used as the autocorrelation interval, and then detecting at least one local extremum in the autocorrelation value on a main orientation of the weaving in order to determine a mean in the observation window for the distance between neighboring parallel yarns.

Abstract: Method and system for non-intrusive measurement of volume density of a specific phase in a part, comprising: processor producing a volume image of the part, the image being formed by a three-dimensional grid of voxels, the values of which indicate the disposition of the specific phase in the part, processor associating a binary coefficient with each voxel of the volume image, thus constructing an initial three-dimensional matrix representation of binary coefficients representing a presence or absence of the specific phase in zones of the part corresponding to the voxels, processor convoluting the initial matrix representation with a convolution matrix kernel corresponding to a predetermined reference volume, the convolution performed by effecting a composition of three (successive) monodimensional convolutions in three independent directions, thus forming a resultant matrix representation, each resultant coefficient of which represents a volume ratio (the density) of the specific phase in the reference volume

Abstract: The method of estimating a quality index of a gray-scale encoded three-dimensional image of a composite material part includes an obtaining step for obtaining a histogram from the image, the histogram representing for each class of a plurality of classes each including at least one gray-scale level, the number of voxels of the image having a gray-scale level belonging to the class; an extraction step for extracting a predetermined number of Gaussian functions present in the histogram; and an estimation step for estimating at least one quality index of the image from parameters characterizing the Gaussian functions extracted from the histogram.

Abstract: Method and system for non-intrusive measurement of volume density of a specific phase in a part, comprising: processor producing a volume image of the part, the image being formed by a three-dimensional grid of voxels, the values of which indicate the disposition of the specific phase in the part, processor associating a binary coefficient with each voxel of the volume image, thus constructing an initial three-dimensional matrix representation of binary coefficients representing a presence or absence of the specific phase in zones of the part corresponding to the voxels, processor convoluting the initial matrix representation with a convolution matrix kernel corresponding to a predetermined reference volume, the convolution performed by effecting a composition of three (successive) monodimensional convolutions in three independent directions, thus forming a resultant matrix representation, each resultant coefficient of which represents a volume ratio (the density) of the specific phase in the reference volume

Abstract: A method of characterizing a part made of woven composite material, includes calculating autocorrelation values of a three-dimensional image in an observation window of the volume of the part for a plurality of spatial vectors used as the autocorrelation interval, and then detecting at least one local extremum in the autocorrelation value on a main orientation of the weaving in order to determine a mean in the observation window for the distance between neighboring parallel yarns.

Abstract: In a method of fast analysis of relief elements featuring on an inner surface of a tire, a three-dimensional image of the surface is captured, and each pixel of the image is assigned a greyscale value proportional to a topographical elevation of a point corresponding to the pixel, so as to obtain a starting image. The image is transformed into an orthogonal reference frame (OXY) in which an abscissa axis (OX) represents circumferential values and an ordinate axis (OY) represents radial values. Each point of the surface, i.e., each pixel, is assigned an altitude gradient value (f(p)) by comparing an elevation of the point with an elevation of a discrete and reduced number of points arranged on a straight line passing through a pixel being considered (p) and oriented in a circumferential direction.

Abstract: A tire appearance detection method includes: capturing an original grey-level image of an inner surface of a tire, and transforming the original image into an orthonormal space with an x-axis (OX) representing a circumferential direction and with a y-axis (OY) representing a radial direction; applying a series of filters to the original image, to obtain a multivariate image; splitting the multivariate image according to a predefined tiling in axial and circumferential directions, to obtain multivariate sub-images of the inner surface of the tire; transforming each of the multivariate sub-images into one-dimensional vectors using selected descriptors, to obtain a simplified multivariate image of the inner surface of the tire; transforming the simplified multivariate image into a common reduced factorial space; and locating sub-images of the inner surface of the tire containing an anomaly using a classifier suitable for identifying an area of the common reduced factorial space containing an anomaly.

Abstract: In a method of fast analysis of relief elements featuring on an inner surface of a tyre, a three-dimensional image of the surface is captured, and each pixel of the image is assigned a greyscale value proportional to a topographical elevation of a point corresponding to the pixel, so as to obtain a starting image. The image is transformed into an orthogonal reference frame (OXY) in which an abscissa axis (OX) represents circumferential values and an ordinate axis (OY) represents radial values. Each point of the surface, i.e., each pixel, is assigned an altitude gradient value (f(p)) by comparing an elevation of the point with an elevation of a discrete and reduced number of points arranged on a straight line passing through a pixel being considered (p) and oriented in a circumferential direction.

Abstract: Detection method according to Claim 9, in which, the grey level image of the inner surface of a tyre to be checked is captured and this original image is transformed into an orthonormal space in which the x-axis (OX) represents the circumferential direction, and the y-axis (OY), the predetermined series of filters is applied to the original image of the inner surface of the tyre to be checked in order to obtain a multivariate original image, the multivariate original image is split according to the predefined tiling in the axial and circumferential directions, in such a way as to obtain multivariate sub-images of the inner surface of the tyre to be checked, each of the multivariate sub-images is transformed into one-dimensional vectors, using each of the selected descriptors, in such a way as to obtain a simplified multivariate image of the inner surface of the tyre to be checked, the simplified multivariate image is transformed into the common reduced factorial space, the sub-images of the inner surface o