The present application is the U.S. national stage of International Patent Application PCT/IB2018/059219 filed internationally on Nov. 22, 2018, which, in turn, claims priority to Italian Patent Application No. 102017000134322 filed on Nov. 23, 2017.
The present invention relates to a graphic adaptation method and system for ceramic supports, specifically tiles.
More in particular, the present invention relates to a graphic adaptation method and system for ceramic supports, specifically tiles, adapted to receive a print performed starting from an original graphic file.
In recent years, the production of ceramics has undergone a revolution in relation to printing technologies. From the traditional method that characterised ceramic decoration until the end of the last century, i.e. rotary printing through silicone cylinders, methods have moved on to a contact-less print based on inkjet printers where an appropriate graphic file, processed and split into one-colour channels, is used as the source for printing on tiles of various sizes through printers provided with printheads arranged along transverse bars.
In general there are two different printing modes:
In both printing modes, the ceramic product obtained can be inspected straight after decoration, at the outlet of the digital printer, or after firing, when it is ready to be boxed.
In general, to be able to successfully inspect the ceramic product, it is necessary to have a comparison model.
If the printing takes place with fixed faces, it is necessary to memorise all the faces by acquiring prints free from defects through a television camera and save them in an archive, in a step called the “learning” step.
At the end of the learning step, each tile of the production, acquired in the same way, can be compared with the images stored in the learning step and then, once the homologous model has been identified and through image processing algorithms, any differences are highlighted, i.e. potential production defects.
Therefore, in fixed face printing, provided with a tile image, it is necessary to identify among all the possible sample images, the one that looks most like it, to be used as a reference image for printing (template).
If the print is casual (random) there is potentially an extremely high number of comparison faces, hence it is impossible to acquire all the comparison faces through television camera.
Therefore, it is impossible to have an effective comparison sample deduced from the direct acquisition of material.
Thus, samples must be obtained by deducing them from the original graphic file that represents the printing source.
In the event of random printing, the acquisition of the sample images determines a multitude of problems, among which one of the most significant ones is a different colour rendering between the source graphic file and the acquired image with probable lack of colour conformity of the final ceramic product to the source graphic file.
It is known that “colour rendering” means the colour assumed by each point of the image, expressed in a known colorimetric system such as, for example, RGB, HSL etc.
Further problems encountered are:
In general, there is a problem of probable inconsistency between the identifying graphic characteristics of the original graphic file and those of the images acquired from the sample ceramic supports.
It follows that the use of the original graphic file (without processing) used for printing to evaluate the correctness thereof a priori (quality control) is impossible.
In solutions of the prior art, furthermore, any defects caused by digital printing, such as dark bands, stripes and the like can only be discovered on the ceramic products, i.e. only after firing and at the outlet from the kiln.
It can be understood how a defective print implies a concrete risk of rejection/declassification of products already fired and ready to be boxed.
The object of the present invention is to provide a method and/or a graphic adaptation system for ceramic supports adapted to receive a print that overcomes the drawbacks of the prior art.
Another object of the present invention is to guarantee a match of the colour range between the original graphic file and the acquired ceramic support.
The object of the present invention is further to provide a method and/or a quality control system for ceramic supports adapted to receive a print that overcomes the drawbacks of the prior art.
In a first aspect, the present invention describes a graphic adaptation method for sample ceramic supports adapted to receive a print, wherein the method comprises the steps of:
Preferably, the step of matching in terms of points comprises seeking a biunique match between sample points, representative of the sample image, and the original points present in the original image file.
Preferably, the step of matching in terms of points envisages seeking a biunique spatial and colour match in terms of points, between sample points, representative of the sample image, and the original points present in the original image file.
Preferably the method comprises the step of:
Preferably the method comprises the step of:
Preferably the method comprises the step of:
Preferably, said step of calculating transformation values comprises the steps of:
Preferably, said step of calculating transformation values further comprises the steps of:
Preferably, said complete mapping is obtained through one of the following:
Preferably, said sample representative values are values of one or more RGB triplets.
Preferably, said complete mapping is obtained via a Look Up Table in which each triplet of the original colour space is associated with one from among mean, mode, median of the samples mapped by the sample colour space, obtained in the preceding step of mapping from said sample representative values to said original representative values.
Preferably, said complete mapping further comprises the steps of:
Preferably, said modifying step f5 of said original image file includes modifying the original image file as a function of said calculated colour transformation, determining said adapted image file.
Preferably, said step of graphically aligning is realised by variation of an original resolution of said original image to the value of a sample resolution of said sample image.
Preferably, said step of printing a plurality of images on sample ceramic supports is realised in a printing mode between random mode and fixed faces mode.
Preferably, said step of printing a plurality of images on ceramic supports comprises:
Preferably, said step of matching in terms of points by printing in random mode is realised for seeking the position in which the sample image is positioned in the original image file.
Preferably, said printing step comprises:
In a second aspect, the invention discloses a quality control method for ceramic supports comprising the steps of:
In a third aspect of the invention, the method of the first aspect of the invention is a computer implemented method.
In a fourth aspect of the invention, the method of the aspect of the invention is a computer implemented method.
In a fifth aspect, the present invention describes a graphic adaptation system for sample ceramic supports adapted to receive a print, wherein the system comprises:
Preferably, said comparing module is configured for matching in terms of points between said sample points and said original points present in said original image file through seeking a biunique match between said sample points, representative of the sample image, and said original points present in the original image file.
Preferably, said comparing module is configured for seeking said match in terms of points between a search for a spatial and colour match, between sample points, representative of the sample image, and the original points present in the original image file.
Preferably, said first processing station comprises an extraction module configured for extracting at least one original image in said original image file corresponding to said sample image as a function of said match in terms of points detected.
Preferably, said first processing station comprises a graphic alignment module configured for graphically aligning said sample image and said at least one original image, as a function of one or more from among the respective resolutions and the respective perspectives.
Preferably, said first processing station comprises a calculating module configured for calculating, in reference to said sample image and to said at least one original image aligned and at the same resolution, transformation values between said sample value of colour rendering and said original value of colour rendering starting from said match in terms of points between said sample points and said original points, adapting the graphic of the original image file to the graphic of the printed ceramic support in terms of colour rendering.
Preferably, said processing station further comprises:
a first identifying module configured for identifying a first sliding window in said original image and a second sliding window in said sample image in which said sliding windows slide in the respective images in a like way;
a second calculating module configured for calculating sample representative values of a sample colour space of said sample image and original representative values of an original colour space of said original image, respectively in each of said second sliding window and said first sliding window;
a mapping module configured for mapping said sample representative values and said original representative values enabling a transformation from said original value of colour rendering to said sample value of colour rendering.
Preferably, said processing station further comprises:
a second identifying module configured for identifying a colour transformation between said sample representative values and said original representative values which is representative of a complete mapping between said sample colour space and said original colour space.
Preferably, said second identification module comprises one or more from among:
a first transformation sub-module configured to identify the colour transformation by means of a linear regression technique;
a second transformation sub-module configured to identify the colour transformation by means of an Artificial Neural Network technique.
Preferably, said second identification module comprises:
a third transformation sub-module configured to identify the colour transformation by means of a technique exploiting a Look Up Table, wherein said second identifying module is configured to:
verify the mapping of the Look Up Table;
if the Look Up Table does not completely map the triplets of the original colour space:
acquire further sample images for mapping a part of the original colour space not yet mapped;
estimate the missing RGB triplets using the 1:1 matches of the Look Up table as parameters for the linear regression system or alternatively for training an artificial neural network.
Preferably, said printer is configured for printing in either the random or fixed faces modes.
In a sixth aspect, the present invention discloses a quality control system for ceramic supports comprising:
a graphic adaptation system according to what is described in the fifth aspect, configured to generate an adapted image file starting from an original image file;
a receiving means for receiving a printed ceramic support;
a classification system, coupled to said graphic adaptation system and to said receiving means for receiving a printed ceramic support, comprising a second processing station comprising:
a research module configured to identify a portion in said adapted image file, corresponding to the graphic reproduced on said printed ceramic support;
a detecting module configured to identify graphic differences between the graphic reproduced on said printed ceramic support and said portion of said adapted image file;
In a seventh aspect, the present invention describes a production system for producing ceramic supports comprising a quality control system for ceramic supports, according to the sixth aspect, interposed between an image printing system on ceramic supports and a kiln for firing said ceramic supports.
In an eighth aspect, the present invention describes a program for a calculator configured, in use, for performing the method of the first aspect of the invention.
In a ninth aspect, the present invention describes a program for a calculator configured, in use, for performing the method of the second aspect of the invention.
The invention achieves the main technical effect of guaranteeing a match of the colour range between the original graphic file and the printed ceramic support.
The technical effect achieved is an efficient extraction of possible production defects, reducing false recognitions.
The technical effects mentioned, advantages cited and other technical effects/advantages of the invention will emerge in further detail from the description provided herein below of an example of embodiment provided by way of approximate and non-limiting example with reference to the attached drawings.
A graphic adaptation system 100 for sample ceramic supports according to the invention comprises, in general, a printer configured for printing a limited plurality of sample ceramic supports starting from an original image file, a colour or b/w image acquiring device configured to acquire a sample image for each sample ceramic product, and a processing station configured for graphically adapting the original image file to the acquired image in terms of colour rendering, resolution and perspective.
With reference to
In general, it should be noted that in the present context and in the claims herein below, the first processing station 10 is presented as being subdivided into distinct functional modules (memory modules or operating modules) for the sole purpose of describing the functions thereof clearly and thoroughly.
Such first processing station 10 can comprise a single electronic device, appropriately programmed to perform the functionalities described, and the different modules can correspond to hardware entities and/or routine software that are part of the programmed device.
Alternatively, or in addition, these functions can be performed by a plurality of electronic devices over which the aforesaid functional modules can be distributed.
The first processing station 10 can also make use of one or more processors for execution of the instructions contained in the memory modules.
Said functional modules can also be distributed over different local or remote computers, depending on the architecture of the network in which they reside.
In particular, in
In other words, the first processing station 10 is configured for loading an original image file F_PRINT representative of an image for printing I_PRINT (
In one embodiment of the invention, specific for fixed face printing, a combination of parts of the graphic coincides with the image for printing I_PRINT.
In another embodiment of the invention, specifically for random printing, the parts of the graphic represent random samples of the image for printing I_PRINT.
The original image file F_PRINT is graphically defined in terms of first identifying graphic characteristics GRAF_1.
Preferably, the first identifying graphic characteristics GRAF_1 comprise one or more from among:
With reference to
In particular the printing can take place in random or fixed faces mode.
The invention envisages a printing step f1 (
According to the prior art of the field of printing on ceramic supports, the printing of the plurality of sample ceramic supports PCS_i is performed in one mode from among the random mode and the fixed faces mode.
It can be understood that step f1 is a production step for producing a limited plurality of sample ceramic supports PCS_j bearing a print bearing the image for printing I_PRINT contained in the original image file F_PRINT.
The terminology “printing on ceramic supports” in technical jargon has the meaning specified in the previous paragraph, and during the description reference will be made to this interpretation unless otherwise indicated.
With reference to the prior art described (pag.2) it is clear that a plurality of ceramic supports is produced in a production line and that, following this, an image is printed onto the plurality of ceramic supports.
With reference to
In one embodiment related to the random printing mode, the image acquiring device 20 is configured to acquire a sample image IM_PCS_j (
In particular, the image acquiring device 20 comprises one or more colour or b/w television cameras, respectively provided for acquiring colour or b/w images.
The sample image IM_PCS_j is graphically defined in terms of second identifying graphic characteristics GRAF_2 depending on the filming device 20.
The second identifying graphic characteristics GRAF_2 comprise one or more from among:
It is to be understood that the first identifying graphic characteristics GRAF_1 are different from the second identifying graphic characteristics GRAF_2, at least in terms of the colour rendering, the former being related to the original image file, the second depending on an “alteration” induced by the image acquiring device 20.
The invention further envisages identifying, within each sample ceramic support image acquired IM_PCS_j, a series of characteristics that characterise the graphic reproduced on the ceramic support.
According to the invention, with reference to
Each of the sample points P2 is characterised by a describer D2 comprising a plurality of characteristic elements, representative of local graphic characteristics of each point, defined as “local features”.
It is required that there be sufficiently numerous sample points selected so as to be able to describe the sample image well.
The first processing station 10 comprises a first selection module 102 (
According to the invention, with reference to
Each of the original points P1 is characterised by a describer D1 comprising a plurality of characteristic elements, representative of local characteristics of each point, defined as “local features”.
It is required that there be sufficiently numerous original points P1 selected so as to be able to describe the sample image well.
The first selection module 102 (
According to the invention, a match seeking step f4.1 is also provided.
In other words, the first processing station 10 is configured to select the sample points (key points) P2 of an acquired ceramic support in which the points are representative of the sample image IM_PCS_j, and for selecting the original points P1 present in the original image file F_PRINT.
With reference to
In other words, the step f4.1 comprises seeking a biunique match between the sample points P2, representative of the sample image IM_PCS_j, and the original points P1 present in the original image file F_PRINT.
In particular, the match M1 is a spatial and colour match in terms of points, between the sample points P2, representative of the sample image IM_PCS_j, and original points P1 present in the original image file F_PRINT.
In particular, for printing in random mode, the matching is performed in order to find the position in which the sample ceramic support PCS_j, is positioned in the original image file F_PRINT.
The first processing station 10 comprises a comparing module 103 (
According to the invention, at this point the original image file F_PRINT is modified so that it matches the sample image in terms of points.
Precisely, the invention comprises a modification step f5 of modifying the original image file F_PRINT starting from the match in terms of points M1 determining an adapted image file F_ADAPT, thus adapting the graphic of the original image file F_PRINT to the graphic of the sample image IM_PCS_j.
An adapting module 107 in the first processing station 10 is configured to perform the described step f5.
According to the invention, the step f5 of modifying the original image file F_PRINT envisages, subsequently to the step f4.1 of matching in terms of points, a step f4.2 of image extraction for identifying in the original image F_PRINT a region of interest ROI that matches the sample image IM_PCS_j printed on the ceramic support.
In other words, the first processing station 10 is configured for matching in terms of points M1 between the sample points P2 and original points P1 present in the original image file F_PRINT.
With reference to
The two images however maintain different identifying graphic characteristics GRAF_1, GRAF_2, in particular different resolution, colour rendering and perspective.
In other words, the first processing station 10 is configured for extracting at least one original image IM_F_PRINT from the original image file F_PRINT that corresponds to the sample image IM_PCS_j as a function of the match in terms of points M1 detected.
According to the invention, a further step f4.3 of graphic realignment is also comprised.
With reference to
The first processing station 10 comprises a graphic realignment module 105 (
In other words, the first processing station 10 is configured for graphically aligning the sample image IM_PCS_j and the at least one original image IM_F_PRINT, so that they are perfectly aligned, as a function of the respective resolutions RS_2, RS_1 and/or the respective perspectives PR_2, PR_1.
According to the invention, the graphic alignment is realised by exploiting the spatial relationship between the coordinates of the sample points P2 in the sample image IM_PCS_j and the coordinates of the original points P1 in the original image IM_F_PRINT.
In other words, the spatial relationship between the coordinates of the sample points P2 and of the original points P1 allows to identify the perspective transformation or the affine transformation (in matrix form) that allows the original image IM_F_PRINT to be aligned with the desired graphic portion of the sample image IM_PCS_j as a function of the respective resolutions RS_1, RS_2 and/or the respective perspectives PR_1, PR_2. In particular, the resolution is defined as a function of the resolutions RS_1, RS_2 and preferably of the quality control algorithms used.
According to the invention, a step f4.4 is also comprised, of conversion of the colour space for adapting the value of colour rendering RC_1 of the original file to the value of colour rendering RC_2 of the sample.
With reference to
The technical effect achieved is an adaptation of the graphic of the original image file F_PRINT to the graphic of the printed ceramic support PC_i in terms of colour rendering.
In other words, starting from the two alignable images at the same resolution, the invention comprises appropriately processing the original graphic, to perform the colour conversion and make it as similar as possible to that of the acquired ceramic support.
The conversion step f4.4 envisages calculating the transformation values V1i→V2i between an original colour space SCO of the original image IM_F_PRINT and a sample colour space SCC of the sample image IM_PCS_j, superposed and at the same resolution.
The transformation values V1i→V2i define the possible transformations between elements of the original colour space SCO of the original image IM_F_PRINT and the sample colour space SCC of the sample image IM_PCS_j.
In a preferred embodiment of the invention, the transformation values V1i→V2i are values of one or more RGB triplets.
The first processing station 10 comprises a first calculating module 106 configured to perform the described step.
In other words, the first processing station 10 is configured for calculating the transformation values V1i→V2i between an original colour space SCO of the original image IM_F_PRINT and a sample colour space SCC of the sample image IM_PCS_j, superposed and at the same resolution.
As shown in
In other words, the invention envisages identifying two windows of settable dimensions (e.g. from 1×1 to 11×11) that slide, respectively, one on the region of interest ROI of the original image IM_F_PRINT, and the other on the acquired sample image IM_PCS_J.
The first calculating module 106 of the first processing station 10 comprises a first identifying module 106a (
In other words, the first processing station 10 is configured for identifying a first sliding window SW_1 in the original image IM_F_PRINT and a second sliding window SW_2 (
The invention comprises, subsequently, the step (f4.4.2) of calculating sample representative values V2i of a sample colour space SCC of the sample image IM_PCS_j and original representative values V1i of an original colour space SCO of the original image IM_F_PRINT, respectively in each of the two sliding windows identified.
In particular, the invention comprises calculating, both for the sliding window SW_1 which slides on the region of interest ROI, and for the like sliding window SW_2 that slides on the sample image one or more transformation values V1i→V2i expressed through RGB triplets.
According to the invention, the sliding windows SW_1, SW_2 are the same respective positions with respect to the respective images when the transformation values V1i→V2i are calculated, preferably expressed as values of RGB triplets.
The first calculating module 106 of the first processing station 10 comprises a second calculating module 106b (
In other words, the first processing station 10 is configured for calculating sample representative values V2i of a sample colour space SCC of said sample image IM_PCS_j and original representative values V1i of an original colour space SCO of the original image IM_F_PRINT, respectively in each of the two sliding windows identified.
The invention comprises, at this point, the step (f4.4.3) of mapping the sample representative values V2i and the original representative values V1i allowing a transformation from the original value of colour rendering RC_1 to the value of colour rendering RC_2 of the sample.
In other words, the invention comprises creating a transformation function between each component of the colour rendering RC_1 of the original graphic and multiple possible values obtained from the acquired image; this is acceptable as, for example, multiple values in the acquired image can correspond to the same mean value of the sliding window SW_1 on the ROI.
The first calculating module 106 of the first processing station 10 comprises a mapping module 106c (
The invention further comprises the step f4.4.4 of identifying a colour transformation TR_OK between the sample representative values V2i and the original representative values V1i which is representative of complete mapping M_OK between said sample colour space SCC and the original colour space SCO.
The first calculating module 106 of the first processing station 10 comprises a second identifying module 106d (
In other words, the first processing station 10 is configured for identifying the colour transformation TR_OK between the original representative values V1i and the sample representative values V2i which is representative of a complete mapping M_OK between the original colour space SCO and the sample colour space SCC.
It is possible that at the end of step f.4.4.4 a RGB triplet of the original colour space SCO is associated with multiple RGB triplets of the sample colour space SCC. Therefore, a generalised transformation is calculated that approximates in the best possible way this multiple mapping.
According to the invention, to obtain complete mapping M_OK, three different solutions are implemented starting from techniques known in literature:
Linear Regression RL: a matrix of coefficients K(1 . . . n) is calculated which is the solution of a system of linear equations formed by the SCO/SCC samples obtained in the preceding mapping step f.4.4.3 from mapping sample representative values V2i to the original representative values V1i.
In particular, as already said, the sample representative values V1i, V2i are values of one or more RGB triplets.
To calculate a prediction of the transformation value of an RGB triplet of the original colour space SCO, this is multiplied by the matrix of coefficients K.
The second identifying module 106d comprises a first transformation sub-module 106d1 configured to identify the colour transformation TR_OK by means of the linear regression technique RL described.
In other words, the first processing station 10 is configured to identify the colour transformation TR_OK by means of the linear regression technique described. Artificial Neural Networks ANN: The matches between the original colour space SCO and the sample colour space SCC obtained in the preceding mapping step f4.4.3 from the sample representative values V2i and the original representative values V1i are used for training an artificial neural network.
To obtain the prediction of the transformation of an RGB triplet of the original colour space SCO into an RGB triplet of the sample colour space SCC the RGB triplet of the original colour space SCO is subjected to transformations by the neural network.
Based on the structure of the network, the triplet undergoes one or more transformations resulting from the network training step and finally the result of the transformation is obtained.
Unlike linear regression the function is not necessarily linear, therefore it allows the transformation from original colour space SCO to sample colour space
The second identifying module 106d comprises a second transformation sub-module 106d2 configured to identify the colour transformation TR_OK by means of the artificial neural network technique described.
In other words, the first processing station 10 is configured to identify the colour transformation TR_OK by means of the artificial neural network technique ANN described.
Look Up Table LUT: each RGB triplet of the original colour space SCO is associated with one from among mean, mode, median of the RGB samples mapped by the sample colour space SCC, obtained in the preceding step f.4.4.3 of mapping from said sample representative values V2i to said original representative values V1i.
This leads to one-to-one mapping between triplets of the original colour space SCO and triplets of the sample colour space SCC.
To obtain a prediction of the transformation value of an RGB triplet of the original colour space, the LUT in the position identified by the RGB triplet of the original colour space SCO is accessed.
The second identifying module 106d comprises a third transformation sub-module 106d3 configured to identify the colour transformation TR_OK by means of the Look Up Table LUT technique described.
In other words, the first processing station 10 is configured to identify the colour transformation TR_OK by means of the Look Up Table LUT technique described. Unlike the two previous solutions that determine a mathematical function for predicting the transformation of each RGB triplet, the LUT may not completely map the triplets of the original colour space SCO.
If this happens:
In other words, according to the invention, therefore, to obtain complete mapping M_OK the following steps are comprised:
Once the transformation function has been obtained, the LUT is populated in the positions identified by the missing RGB triplets of the original colour space SCO with the linear regression or artificial neural network predictions.
The second identification module 106d is (
In other words, the first processing station 10 is configured to check whether the LUT does not completely map the triplets of the original colour space SCO, acquire further sample images of real tiles for mapping a part of the original colour space SCO not yet mapped, and to estimate the missing triplets using the 1:1 matches of the LUT as parameters for the linear regression system or alternatively for training an artificial neural network.
With reference to
The technical effect achieved is a graphic adaptation of the original image file F_PRINT to the graphic of the sample image IM_PCS_j of the acquired ceramic support PC_i in terms of colour rendering.
The invention provides the main technical effect of an optimal graphic/colour match between the appropriately processed original graphic file and the image acquired by means of the acquisition system, of the printed ceramic support.
The invention, as described, further has some technical effects; the two images, having very slight differences in colorimetric terms, but only attributable to the production process, can be used to evaluate the correctness of the graphic/decoration, i.e. in other words, to check the quality of the ceramic supports produced.
Appropriate image processing algorithms, having two very similar images to each other, can extract the differences between them, classify them based on size, shape, type, etc. determining an acceptability classification or not.
In an automatic inspection system, such procedure drastically reduces the time of the setup step and guarantees greater reliability in the extraction of possible production defects, reducing false recognitions thereof.
In fact, to reach these technical effects, the invention comprises a quality control method for ceramic supports PC_i.
The method comprises the steps of:
To actuate the method, the invention comprises (
the graphic adaptation system 100, previously described, configured to generate an adapted image file F_ADAPT starting from the original image file F_PRINT; receiving means 400 of a printed ceramic support PC_i;
a classification system 300, coupled to the graphic adaptation system 100 and to the receiving means 400 of a printed ceramic support PC_i, comprising a second processing station 110 (
For the second processing station 110 the same structural/functional/module considerations expressed in relation to the first processing station 10, on pages 6 and 7 are valid.
The second processing station 110 comprises:
For example, the classification module 113 classifies the tiles into a plurality of classes among which one class C1 is representative of first choice tiles, one class C2 is representative of second choice tiles and one class C3 is representative of third choice tiles.
The detected differences Dd that determine the classification are global differences in terms of colour and local defects such as missing decorations, presence of drops of colour, presence of lines of colour, missing graphic parts, impurities, evaluated based on shape, position, size, intensity, etc.
Preferably the graphic adaptation system 100 and the classification system 300 are provided on a same machine; in other words, the quality control system 200 is monolithic.
Alternatively, the graphic adaptation system 100 and the classification system 300 are provided on different machines; in other words, the quality control system 200 is distributed.
In this second case, the image acquisition devices of the two systems are calibrated between each other in the colour space so as to be able to indistinctly use the adapted image file F_ADAPT.
Furthermore, this technique, mainly devised for the quality control of ceramic supports decorated with random printing techniques, can also be used in the case of fixed face printing, avoiding printing all the necessary samples for comparison, allowing them to be constructed digitally starting from the original graphics of each face.
In a further aspect, the invention comprises a production system for producing ceramic supports comprising a quality control system for ceramic supports PC_i, interposed between an image printing system on ceramic supports PC_i and a kiln for firing the ceramic supports themselves.
In particular, the quality control system is the system 100 described above.
Number | Date | Country | Kind |
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102017000134322 | Nov 2017 | IT | national |
Filing Document | Filing Date | Country | Kind |
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PCT/IB2018/059219 | 11/22/2018 | WO | 00 |
Publishing Document | Publishing Date | Country | Kind |
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WO2019/102391 | 5/31/2019 | WO | A |
Number | Name | Date | Kind |
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9704236 | Kogan et al. | Jul 2017 | B2 |
20030208345 | O'Neill | Nov 2003 | A1 |
20130148912 | Chong | Jun 2013 | A1 |
20140192373 | Maccari | Jul 2014 | A1 |
Number | Date | Country |
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203 061 453 | Jul 2013 | CN |
Entry |
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Lopez, F., et al. “A Study of Registration Methods for Ceramic Tile Inspection Purposes.” Jan. 1, 1999, ISBN: 978-0-8478-2227-0 Retrieved from the Internet: https://www.researchgate.net/publication/240626869_A_Study_of_Registration_Methods_for_Ceramic_Tile_ Inspection_Purposes [retrieved May 21, 2020]. 6 pages. |
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Number | Date | Country | |
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20200349403 A1 | Nov 2020 | US |