A method for detecting and compensating for defective printing nozzles in an inkjet printing machine includes printing test sheets each including at least one printing nozzle test chart and at least one gray area for every color separation. The test sheets are recorded and digitized with subsequent pixel-nozzle mapping and amplitude/phase value determination by using a computer. Current measurements are taken at the printing nozzles in between test sheets and customer sheets while being printed. The computer is used for teaching in a SVM model with the results of the current measurement and pixel-nozzle mapping and amplitude/phase determination. The taught-in SVM model and the current measurements are applied to printed, recorded and digitized customer's images to detect defective printing nozzles during production printing on the inkjet printing machine and the detected defective printing nozzles are compensated for.

An information processing device configured to make a printing device execute printing includes a storage section configured to store special color data representing a special color included in a print target image, and a processing section configured to make the printing device print a special color patch as a color patch of the special color included in the print target image based on the special color data to obtain a colorimetric value of the special color patch. Based on the print target image and the special color data, the processing section makes the printing device execute printing of the special color patch in accordance with output of a print image based on the print target image.

System and methods for matching color and appearance of a target coating are provided herein. The system includes an electronic imaging device configured to receive a target image data of the target coating. The target image data includes target coating features. The system further includes one or more feature extraction algorithms that extracts the target image features from the target image data. The system further includes a machine-learning model that identifies a calculated match sample image from a plurality of sample images utilizing the target image features. The machine-learning model includes pre-specified matching criteria representing the plurality of sample images for identifying the calculated match sample image from the plurality of sample images. The calculated match sample image is utilized for matching color and appearance of the target coating.

The invention relates to a method for online quality control of decorative prints on substrate materials, including similarity comparisons of actual and target images and adjusting decorative prints if deviations of color values are detected. The method may include the steps of: a) producing a hyperspectral digital image of a print decoration; b) calibrating the print decoration via a hyperspectral digital image; c) producing and storing a digital target image of the print decoration; d) creating a first print decoration on a first substrate material; e) producing and storing a digital actual image of the printed decoration on the first substrate material; f) determining color deviations between the digital target image and the digital actual image via a computer program; and g) printing on at least one side of substrate materials so as to form a decorative layer. The invention also relates to a device for carrying out the method.

Processor implemented systems and methods for matching color and appearance of a target coating are provided herein. A system includes a storage device for storing instructions, and one or more data processors. The data processor(s) are configured to execute instructions to receive a target image of a target coating. The data processor(s) are also configured to apply a feature extraction analysis process that divides the target image into a plurality of target pixels for image analysis.

A method performed by an image forming apparatus is provided. The method includes receiving an input of selecting a first color from a first color image, scanning, a reference image including at least one reference color that is used to reproduce a color, receiving an input of selecting a second color from the at least one reference color, based on scan color data in which characteristics of the image forming apparatus obtained by scanning a color compensation chart representing a color space have been reflected, determining a second color scan value of the second color as a second color value of the second color from which the characteristics of the image forming apparatus have been removed, and converting a first color value of the first color into the second color value of the second color and outputting the first color image having the second color instead of the first color.

A method for detecting and compensating for defective printing nozzles in an inkjet printing machine includes printing test sheets each including at least one printing nozzle test chart and at least one gray area for every color separation. The test sheets are recorded and digitized with subsequent pixel-nozzle mapping and amplitude/phase value determination by using a computer. Current measurements are taken at the printing nozzles in between test sheets and customer sheets while being printed. The computer is used for teaching in a SVM model with the results of the current measurement and pixel-nozzle mapping and amplitude/phase determination. The taught-in SVM model and the current measurements are applied to printed, recorded and digitized customer's images to detect defective printing nozzles during production printing on the inkjet printing machine and the detected defective printing nozzles are compensated for.

There is provided with an information processing apparatus. A first obtaining unit obtains data of a reference image indicating a target of printing output to be performed by a printing apparatus. A second obtaining unit obtains data of an image printed by the printing apparatus. A correcting unit corrects a local image density difference or the reference image based on a global image density difference between the reference image and the printed image. An evaluating unit evaluates quality of the printed image based on the local image density difference between the corrected reference image and the printed image.

An information processing apparatus is configured to perform: acquiring target image data representing a target image made up of a plurality of partial images; determining whether a specific condition is met for each of the plurality of partial images; selecting a direction-determining method of a printing direction for each of the plurality of partial images in accordance with a determination result; determining whether the selected direction-determining method matches a correct method; and adjusting condition data for controlling a printing device so as to increase selectability of the correct method in response to determining that the selected direction-determining method differs from the correct method. The specific condition indicates that an image evaluation value be greater than or equal to a threshold. The image evaluation value represents an expected color difference between a first image printed by a first-directional partial print and a second image printed by a second-directional partial print.

An image processing apparatus comprises a unit configured to set a color selected by a user from among colors included in scanned image data obtained by reading a reference sample as a destination color for the adjustment-target color. Then, the unit configured to set a destination color has a function to set the destination color based on first scanned image data obtained by reading a color sample as the reference sample, in which patches of a plurality of colors including colors around the adjustment-target color are printed and a function to set the destination color based on second scanned image data obtained by reading a sample document.