Printability evaluation device and printability evaluation method

Abstract

To provide a printability evaluation device and printability evaluation method, which enable objective and accurate evaluation of printability of a printing target matter.SOLUTION: A printability evaluation device EA for evaluating printability of a printing target is provided, the device comprising image acquisition means 21 configured to acquire a captured image of a printed image printed on the printing target, brightness value acquisition means 22 configured to acquire brightness values of the captured image acquired by the image acquisition means 21, skewness computation means 23 configured to compute skewness of the brightness values acquired by the brightness value acquisition means 22, and evaluation means 24 configured to evaluate printability of the printing target on the basis of the skewness computed by the skewness computation means 23.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a printability evaluation device and a printability evaluation method. [Background technology]

[0002] BACKGROUND ART Printability evaluation methods for evaluating the printability of a printing object are known (see, for example, Patent Documents 1 and 2). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-70732 [Patent Document 2] Japanese Patent Publication No. 2020-90612 Summary of the Invention [Problem to be solved by the invention]

[0004] The evaluation methods described in Patent Documents 1 and 2 evaluate printability by visually checking the quality of the print applied to the printing object, which has the disadvantage that the evaluation varies depending on the evaluator's subjectivity, making it impossible to objectively and accurately evaluate the printability of the printing object.

[0005] An object of the present invention is to provide a printability evaluation device and a printability evaluation method that can objectively and accurately evaluate the printability of a printing object. [Means for solving the problem]

[0006] A printability evaluation device according to one aspect of the present invention is a printability evaluation device that evaluates the printability of a print object, and includes an image acquisition means that acquires a captured image of a print image printed on the print object, a luminance value acquisition means that acquires a luminance value of the captured image from the captured image acquired by the image acquisition means, a skewness calculation means that calculates the skewness of the luminance value acquired by the luminance value acquisition means, and an evaluation means that evaluates the printability of the print object based on the skewness calculated by the skewness calculation means.

[0007] In the printability evaluation device according to one aspect of the present invention, the evaluation means may evaluate the printability as good when the absolute value of the skewness is equal to or greater than a first threshold value that is greater than zero and equal to or less than a second threshold value that is greater than the first threshold value.

[0008] In one aspect of the printing suitability evaluation device of the present invention, the evaluation means may evaluate the printing suitability using a trained model that has been machine-learned using as training data the ink density of a print image printed on a training printing object, the skewness of the brightness values ​​of a training image obtained by capturing the print image, and the evaluation result of the printing suitability for the training printing object.

[0009] A printability evaluation method according to one aspect of the present invention is a printability evaluation method for evaluating the printability of a print object, and includes an image acquisition step for acquiring a captured image of a print image printed on the print object, a brightness value acquisition step for acquiring a brightness value of the captured image from the captured image acquired in the image acquisition step, a skewness calculation step for calculating the skewness of the brightness value acquired in the brightness value acquisition step, and an evaluation step for evaluating the printability of the print object based on the skewness calculated in the skewness calculation step. [Effects of the Invention]

[0010] According to one aspect of the present invention, printability is evaluated based on the degree of distortion of the brightness values ​​of an image captured of a printed image printed on a printing object, so that the evaluation does not change depending on the evaluator's subjectivity, and the printability of the printing object can be evaluated objectively and accurately. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is an explanatory diagram of a printability evaluation system according to an embodiment. [Figure 2] FIG. 1 is an explanatory diagram of a printability evaluation method according to an embodiment. [Figure 3] FIG. 10 is a diagram showing an example of a histogram of brightness values. [Figure 4] FIG. 10 is a diagram showing an example of a histogram of brightness values. [Figure 5] FIG. 10 is a diagram showing skewness and evaluation results. [Figure 6] An explanatory diagram of a method for generating a trained model for evaluating printability. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. [Device configuration] 1, the printability evaluation device EA is a device that evaluates the printability of printing objects such as printing paper and printing film, and is configured with a computer such as a personal computer or server. The printability of a printing object refers to the performance required of the printing object in order to print with the required resolution and color development, and includes the ink receptivity, drying property, oil absorption property, etc. of the printing object. The printability evaluation apparatus EA includes a storage means 10, a processing means 20, and an operation means 30, and together with a printing means 40, an imaging means 50, and an output means 60, constitute a printability evaluation system EA1.

[0013] The storage means 10 is configured with a memory, a hard disk, etc., and stores various programs for controlling the printability evaluation device EA and the printability evaluation system EA1. In this embodiment, the storage means 10 also stores a skewness threshold value used to evaluate the printability of the printing object.

[0014] The processing means 20 is configured by a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), and includes an image acquisition means 21, a brightness value acquisition means 22, a skewness calculation means 23, and an evaluation means 24.

[0015] The image acquisition means 21 acquires a captured image of a print image printed on a printing object from the imaging means 50. Examples of the print image include an image, a character, a pattern, an identifier, and a test print pattern.

[0016] The brightness value acquisition means 22 acquires the brightness value of the captured image acquired by the image acquisition means 21 from the captured image.

[0017] The distortion calculation means 23 calculates the distortion of the brightness values ​​acquired by the brightness value acquisition means 22. The distortion is calculated by multiplying the number of pixels in the captured image by n and the brightness value of each pixel by x i When the average value of the brightness values ​​is x bar and the standard deviation of the brightness values ​​is s, it is calculated using the following formula 1.

[0018]

number

[0019] The evaluation means 24 evaluates the printability of the printing object based on the skewness calculated by the skewness calculation means 23.

[0020] The operation means 30 is composed of a keyboard, an operation panel, a touch panel, a mouse, various switches, a microphone for voice input operation, etc., and is capable of inputting operation signals from various operations into the printability evaluation device EA and the printability evaluation system EA1. For example, the ink density of printing on the printing object is set via the operation means 30, and the operation signal is sent to the processing means 20 and the printing means 40 together with the set value of the ink density.

[0021] The printing means 40 is composed of an inkjet printer, laser printer, thermal printer, dot printer, offset printing machine, letterpress printing machine, intaglio printing machine, screen printing machine, etc., and is capable of sending and receiving various signals to and from the processing means 20.

[0022] The imaging means 50 is composed of a camera, a camera, a microscope with an imaging function, an imaging sensor, etc., and is capable of transmitting and receiving captured images and various signals to and from the processing means 20.

[0023] The output means 60 is composed of display devices such as displays or panels, and notification devices such as indicator lights or speakers, and is configured to output the evaluation results from the printability evaluation device EA on a screen or by lighting up or making sounds, etc.

[0024] [Printability evaluation method] A printability evaluation method performed in the following procedure shown in FIG. 2 will be described using the printability evaluation system EA1 equipped with the printability evaluation device EA described above as an example. First, a user of the printability evaluation system EA1 (hereinafter simply referred to as "user") sets the ink density of the print to be applied to the print object via operation means 30, and then inputs a signal to start automatic operation via operation means 30. Next, when the user or a transport means (not shown), such as an articulated robot or a belt conveyor, places the print object in a predetermined position, processing means 20 drives printing means 40 to print on the print object with the set ink density (step ST11). Thereafter, processing means 20 drives imaging means 50 to capture an image of the print image printed on the print object (step ST12).

[0025] Next, the image acquisition means 21 acquires a captured image of the print image from the imaging means 50 (step ST13). Then, the luminance value acquisition means 22 acquires the luminance value of each pixel of the captured image acquired in step ST13 (step ST14). In this embodiment, the luminance value acquisition means 22 performs grayscale processing on the captured image and then acquires the luminance value of each pixel. Next, the skewness calculation means 23 calculates the skewness of the luminance values ​​acquired in step ST14 (step ST15).

[0026] Thereafter, the evaluation means 24 evaluates the printability of the printing object based on the skewness calculated by the skewness calculation means 23, and outputs the evaluation result to the output means 60 (step ST16). In this embodiment, the evaluation means 24 evaluates the printability of the printing object by comparing the calculated skewness with a threshold value stored in the storage means 10. The evaluation means 24 also classifies the printability into two levels and determines whether the printability is good (pass) or poor (fail). Next, the output means 60 outputs the printability evaluation result and notifies the user by displaying it on a display device, turning on an alarm device, or emitting a sound from the alarm device (step ST17).

[0027] If printing is performed so that the area of ​​the ink-free base and the area of ​​the ink-covered portion of the printed image are equal, and the ink in the ink-covered portion maintains its dot shape, the base and the ink-covered portion will be clearly distinguishable. In this case, the histogram of brightness values ​​will exhibit a bimodal distribution with two peaks, as shown in Figure 3, which deviates from a normal distribution, and the skewness value will move away from zero. Therefore, if |skewness| > threshold, the printability will be evaluated as good.

[0028] On the other hand, even if printing is performed so that the area of ​​the ink-free base is equal to the area of ​​the ink-covered area, if the ink bleeds, a gradation caused by the ink will form on the base, fading the boundary with the ink-covered area and making the base and ink-covered area less clearly distinguishable. In this case, the histogram of brightness values ​​will approach a normal distribution with a single peak, as shown in Figure 4, and the skewness value will approach zero. Therefore, if |skewness| ≒ 0, the printability will be evaluated as poor. Note that the frequency shown on the vertical axis in Figures 3 and 4 is the number of pixels having that brightness value divided by the number of pixels in the entire image.

[0029] Furthermore, if the skewness is excessively large, for example, it may be because the ink density is too high and the ink is adhered excessively, or because the ink density is too low and the ink is not adhered at all, or because the ink density is appropriate but the substrate repels the ink too much and the ink is not adhered at all, resulting in an excessively large area of ​​substrate where ink is not adhered or an excessively large area of ​​ink-adhered areas. For this reason, if |skewness|>>0 (|skewness| is sufficiently greater than zero), the printability is evaluated as poor.

[0030] In this embodiment, if the absolute value of the skewness is equal to or greater than a first threshold value greater than zero and equal to or less than a second threshold value greater than the first threshold value, the printability of the printing object is evaluated as good, and if not, the printability is evaluated as poor. Specifically, the first threshold value is set to 0.1, the second threshold value is set to 0.4, and if 0.1≦|skewness|≦0.4, the printability is evaluated as good, and if |skewness|<0.1 or |skewness|>0.4, the printability is evaluated as poor.

[0031] [Evaluation example] As the printing target, various polyvinyl chloride film samples 1 to 11 with different product numbers were used, and their printability was evaluated. First, the same color photograph was printed using the same inkjet printer on Samples 1 to 11. In this case, it is preferable to adjust the ink density so that the area of ​​the ink-free base and the area of ​​the ink-covered portion in the printed color photograph image are equal, and in this evaluation example, the ink density was set to CMYK100.

[0032] Next, the color photographs printed on Samples 1 to 11 were visually inspected for print quality, and then a portion of each color photograph was imaged at 100x magnification using a digital optical microscope. Each image was then subjected to grayscale processing, and the brightness value of each pixel in the image was obtained from the image data. The skewness of the brightness values ​​for each image was then calculated using Equation 1. The calculated skewness and the results of the visual inspection of print quality are shown in Table 1 and Figure 5. The histogram for Sample 9 is shown in Figure 3, and the histogram for Sample 2 is shown in Figure 4.

[0033] [Table 1]

[0034] As shown in Table 1 and Figure 5, Samples 5 to 10, which were evaluated as having good printability (0.1 ≦ |skewness| ≦ 0.4), were confirmed to have good printability even by visual inspection, while Samples 1 to 4 and 11, which were evaluated as having poor printability (|skewness| < 0.1 or |skewness| > 0.4), were confirmed to have poor printability even by visual inspection.

[0035] According to the above-described embodiment, printability is evaluated based on the degree of distortion of the brightness values ​​of an image captured of a print image printed on a printing object, so the evaluation does not change depending on the evaluator's subjectivity, and the printability of the printing object can be evaluated objectively and accurately.

[0036] Furthermore, if the absolute value of the skewness is greater than or equal to a first threshold and less than or equal to a second threshold that is greater than the first threshold, the printability of the object to be printed is evaluated as good. Therefore, the printability of the object to be printed can be evaluated using a simple method of comparing the absolute value of the skewness with a threshold.

[0037] As described above, the best configurations, methods, and the like for implementing the present invention have been disclosed in the above description, but the present invention is not limited thereto. That is, although the present invention has been particularly illustrated and described mainly with reference to specific embodiments, those skilled in the art can make various modifications to the above-described embodiments in terms of shape, material, quantity, and other detailed configurations without departing from the scope of the technical idea and purpose of the present invention. Furthermore, the above-disclosed descriptions limiting the shape, material, and the like are provided as examples to facilitate understanding of the present invention and are not intended to limit the present invention. Therefore, descriptions using names of components that are free from some or all of the limitations on shape, material, and the like are included in the present invention.

[0038] For example, the storage means 10 may be built into the printability evaluation apparatus EA, or may be of a type that is externally attached to the printability evaluation apparatus EA. When the evaluation means 24 evaluates the printability of a printing object using a trained model based on machine learning, the storage means 10 may store the trained model.

[0039] The image acquisition means 21 may acquire the captured image of the printed image printed on the printing object directly from the imaging means 50, or it may not acquire the captured image directly from the imaging means 50, and may acquire the captured image from an image storage means such as a server or database in which the captured images by the imaging means 50 are stored.

[0040] The brightness value acquisition means 22 may acquire brightness values ​​after performing grayscale processing on the captured image, or may acquire brightness values ​​without performing grayscale processing on the captured image.

[0041] The evaluation means 24 may set the skewness threshold for evaluating printability (pass / fail printability) to a value other than 0.1 or 0.4, or may divide the printability into three or more levels depending on the skewness value. For example, if 0.2≦|skewness|≦0.3, the printability may be evaluated as excellent (pass); if 0.1≦|skewness|<0.2 or 0.3<|skewness|≦0.4, the printability may be evaluated as good (pass); and if |skewness|<0.1 or |skewness|>0.4, the printability may be evaluated as poor (fail); the range of |skewness|=0.1 to 0.4 may be divided into 10 parts, for example, every 0.03, and the printability may be evaluated on a 10-point scale; or the skewness value may be output directly as the evaluation result. The evaluation means 24 may change the threshold value of the skewness depending on the ink density.

[0042] The evaluation means 24 may use a trained model that has been machine-learned using skewness and ink density as feature quantities, and evaluate the printability of the printing object based on the skewness calculated by the skewness calculation means 23. That is, in the above embodiment, the skewness calculated in step ST15 is compared with a threshold value in step ST16 to evaluate printability, whereas the skewness and ink density calculated in step ST15 may be input into the trained model in step ST16 to evaluate printability.

[0043] The trained model is generated by machine learning using as training data the ink density of the printed image printed on the training printing object, the skewness of the brightness values ​​of a training image of the printed image, and the evaluation results of the printability obtained by visually inspecting the printed image of the training printing object, as training data. The trained model is generated by the following procedure shown in Figure 6.

[0044] First, printing objects of various types and compositions are prepared for learning, and printing is performed on these printing objects for learning (step ST21). Printing may be performed by printing means 40 or by means other than printing means 40, and there are no particular restrictions on the shape, size, color, etc. of the print image printed on the printing object, but it is preferable to adjust the ink concentration so that the area of ​​the base where ink is not attached and the area of ​​the ink-attached portion are approximately the same.

[0045] Next, the quality of the print image printed on the learning printing object is visually confirmed, and the printing characteristics of the learning printing object are evaluated (step ST22). After that, the print image of the learning printing object is captured and used as a teacher image (step ST23). The image may be captured by the imaging means 50 or by a device other than the imaging means 50. Next, the luminance value of each pixel is acquired from the teacher image captured in step ST23 (step ST24), and skewness is calculated as a feature from these luminance values ​​(step ST25). Then, machine learning is performed using the ink density of the print image printed on the learning printing object, the skewness calculated from the teacher image, and the evaluation result of printability evaluated in step ST22 as teacher data, and a trained model is generated that inputs the ink density of the print image printed on the printing object and the skewness of the luminance values ​​of the captured image and outputs the printability of the printing object (step ST26). In generating a trained model, the order of performing step ST22 and steps ST23 to ST25 is not particularly limited, and steps ST23 to ST25 may be performed after performing step ST22, or step ST22 may be performed after performing steps ST23 to ST25. Specific machine learning techniques are not particularly limited and may include various known techniques such as neural networks, support vector machines, nearest neighbor methods, random forests, stochastic gradient methods, and kernel approximations.

[0046] The operation means 30 may be configured to be separable from the printability evaluation apparatus EA, or may be configured to be inseparable. The operation means 30 may or may not be provided in the printability evaluation device EA or the printability evaluation system EA1, and if it is not provided, an operation signal from an external input device may be input to the printability evaluation device EA or the printability evaluation system EA1.

[0047] The printing means 40 may or may not be provided in the printability evaluation device EA or the printability evaluation system EA1, and if it is not provided, printing may be performed on the printing object by an external printing device that can communicate with the printability evaluation device EA or the printability evaluation system EA1.

[0048] The imaging means 50 may capture the printed image of the printing object in color or in black and white, or may capture a part of the printed image or the entire printed image. The imaging means 50 may or may not be provided in the printability evaluation device EA or the printability evaluation system EA1, and if it is not provided, the image acquisition means 21 may acquire an image captured by an external imaging device that can communicate with the printability evaluation device EA or the printability evaluation system EA1.

[0049] The output means 60 may or may not be provided in the printability evaluation device EA or the printability evaluation system EA1, and if it is not provided, the evaluation results may be output to an external output device that can communicate with the printability evaluation device EA or the printability evaluation system EA1.

[0050] The ink density may be set via the operating means 30 and sent to the processing means 20 or the printing means 40, or the ink density value may be attached to the printing object directly by the printing means 40, or converted into a barcode or QR code (registered trademark), etc., which is then read by the imaging means 50, a barcode reader, a QR code reader, etc. and sent to the processing means 20.

[0051] There are no particular limitations on the type, material, composition, etc. of the printing object. For example, the printing object may be a substrate surface such as paper, film, adhesive sheet, or pressure-sensitive adhesive sheet, or a print-receiving layer such as a coating layer provided on the substrate surface, and the material may be resin, metal, wood, ceramic, etc.

[0052] The means and steps of the present invention are not limited in any way as long as they can perform the operations, functions, or steps described for those means and steps, and are in no way limited to the components and steps of a single embodiment shown in the above embodiment. For example, the image acquisition means may be any means capable of acquiring a captured image of a print image printed on a printing object, and is not limited in any way as long as it is within the scope of the common general technical knowledge at the time of filing (the same applies to other means and steps). [Explanation of symbols]

[0053] EA: Printability evaluation device 10...Memory means 20...Processing means 21...Image acquisition means 22...Luminance value acquisition means 23...Skewness calculation means 24...Evaluation methods 30...Operation means 40...Printing means 50...imaging means 60...Output means

Claims

1. A printability evaluation device that evaluates the printability of a printing object, comprising: an image acquisition means for acquiring a captured image of a print image printed on the printing object; a brightness value acquisition means for acquiring a brightness value of the captured image from the captured image acquired by the image acquisition means; a skewness calculation means for calculating a skewness of the luminance value acquired by the luminance value acquisition means; an evaluation means for evaluating the printability of the printing object based on the skewness calculated by the skewness calculation means, The printability evaluation device is characterized in that the evaluation means evaluates the printability as good when the absolute value of the skewness is equal to or greater than a first threshold value that is greater than zero and equal to or less than a second threshold value that is greater than the first threshold value.

2. A printability evaluation device for evaluating the printability of a printing object, comprising: an image acquisition means for acquiring a captured image of a print image printed on the printing object; a brightness value acquisition means for acquiring a brightness value of the captured image from the captured image acquired by the image acquisition means; a skewness calculation means for calculating the skewness of the luminance values ​​acquired by the luminance value acquisition means; an evaluation means for evaluating the printability of the printing object based on the skewness calculated by the skewness calculation means, The printability evaluation device is characterized in that the evaluation means evaluates the printability using a trained model that has been machine-trained using as training data the ink density of a print image printed on a learning print object, the skewness of the brightness values ​​of a training image obtained by capturing the print image, and the evaluation result of the printability for the learning print object.

3. A printability evaluation method for evaluating the printability of a printing object, comprising: an image acquisition step of acquiring a captured image of a print image printed on the printing object; a brightness value acquiring step of acquiring a brightness value of the captured image from the captured image acquired in the image acquiring step; a skewness calculation step of calculating skewness of the luminance values ​​acquired in the luminance value acquisition step; an evaluation step of evaluating the printability of the printing object based on the skewness calculated in the skewness calculation step; a printability evaluation method characterized in that, in the evaluation step, the printability is evaluated to be good if the absolute value of the skewness is equal to or greater than a first threshold value that is greater than zero and equal to or less than a second threshold value that is greater than the first threshold value.

4. A printability evaluation method for evaluating the printability of a printing object, comprising: an image acquisition step of acquiring a captured image of a print image printed on the printing object; a brightness value acquiring step of acquiring a brightness value of the captured image from the captured image acquired in the image acquiring step; a skewness calculation step of calculating skewness of the luminance values ​​acquired in the luminance value acquisition step; an evaluation step of evaluating the printability of the printing object based on the skewness calculated in the skewness calculation step; In the evaluation step, the printability is evaluated using a trained model that has been machine-learned using training data that includes the ink density of the print image printed on the training print object, the skewness of the brightness values ​​of a training image obtained by capturing the print image, and the evaluation results of the printability for the training print object.

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