Abstract: Certain examples relate to a method of printing management. An image is received for printing and printing parameters to print the image are determined. The image is printed onto a substrate using the printing parameters, and the image is printed with an embedded code corresponding to the printing parameters. The printing parameters are associated with the embedded code such that the printing parameters are retrievable from the embedded code.

Abstract: Certain examples described herein relate to the control of colorants and treatments for printing. In certain examples image data, a colorant color mapping and one or more treatment color mappings is obtained. The colorant color mapping may be used to map the image data to colorant application values. The one or more treatment color mappings may be used to map the image data to treatment application values. The colorant application values and treatment application values may be used to generate discrete print control instructions to apply the set of colorants and set of treatments to a printing substrate.

Abstract: A method is disclosed. According to some examples, the method comprises determining, by processing circuitry, a first element set to be associated with a print addressable location, the first element set comprising a first plurality of elements, wherein each element of the first plurality of elements identifies a print colorant or print colorant combination and is associated with a probability that the print colorant or print colorant combination identified by that element is to be applied to the associated print addressable location.

Abstract: Certain examples relate to a method of printing management. An image is received for printing and printing parameters to print the image are determined. The image is printed onto a substrate using the printing parameters, and the image is printed with an embedded code corresponding to the printing parameters. The printing parameters are associated with the embedded code such that the printing parameters are retrievable from the embedded code.

Abstract: Example methods and systems are described in which a color space vector is transformed into a Neugebauer primary area coverage (NPac) vector, to be used for printing. In some examples, the color space vector is transformed into a NPac vector on the basis of criteria associated to amounts or probabilities of Neugebauer primaries (NPs).

Abstract: Example methods and systems are described in which a color space vector is transformed into a Neugebauer primary area coverage (NPac) vector, to be used for printing. In some examples, the color space vector is transformed into a NPac vector on the basis of criteria associated to amounts or probabilities of Neugebauer primaries (NPs).

Abstract: Example methods of controlling printing of a halftone image are disclosed as well as apparatuses and computer-readable storage mediums relating thereto. In an example, the method includes receiving input data indicating a first colorant deposition order for a colorant combination and a second colorant deposition order for the colorant combination, wherein the second colorant deposition order is different from the first colorant deposition order. Control data is generated based on the input data. The control data includes first pixel data associating a first pixel in the halftone image with the first colorant deposition order, and second pixel data associating a second pixel in the halftone image with the second colorant deposition order. The control data is used to control a printer to print the halftone.

Abstract: Example methods of controlling printing of a halftone image are disclosed as well as apparatuses and computer-readable storage mediums relating thereto. In an example, the method includes receiving input data indicating a first colorant deposition order for a colorant combination and a second colorant deposition order for the colorant combination, wherein the second colorant deposition order is different from the first colorant deposition order. Control data is generated based on the input data. The control data includes first pixel data associating a first pixel in the halftone image with the first colorant deposition order, and second pixel data associating a second pixel in the halftone image with the second colorant deposition order. The control data is used to control a printer to print the halftone. The above amendments are reflected in the attached substitute specification shown in clean and marked-up form in the Appendix submitted herewith.

Abstract: Example implementations relate to random wave mask generation. Some examples may distribute data points in a mask area based on a probability density function. The probability density function may have a maximum probability density located at a first edge and a second edge of the mask area. Some examples may also identify a wave curve that fits the data points. The wave curve may include oscillating waveforms of varying amplitudes. Some examples may also generate a random wave mask based on the wave curve.

Abstract: Certain methods and systems are described to provide color modelling. This color modelling applies to halftone images. In one example, a correction parameter for a color model is determined by minimizing a distance metric between a set of estimated spectral reflectance values and a set of measured spectral reflectance values to generate a multi-dimensional correction parameter. This enables a color model to be used to map at least one Neugebauer Primary area coverage value to at least one spectral reflectance value.

Abstract: Example implementations relate to swath height error compensation. Some examples may determine a density of an image to be printed in an overlap area of a printing material. The overlap area may include target pixels capable of being printed by a first set of drop ejection elements and a second set of drop ejection elements that are redundant to the first set of drop ejection elements. Some implementations may also determine a mask to apply to the first and second set of drop ejection elements based on the determined density, and the mask may designate at least one additional drop to apply to at least one target pixel in the overlap area by at least one of the first and second set of drop ejection elements. Some implementations may also apply the mask to the first set of drop ejection elements and the second set of drop ejection elements.

Abstract: Example implementations relate to random wave mask generation. Some examples may distribute data points in a mask area based on a probability density function. The probability density function may have a maximum probability density located at a first edge and a second edge of the mask area. Some examples may also identify a wave curve that fits the data points. The wave curve may include oscillating waveforms of varying amplitudes. Some examples may also generate a random wave mask based on the wave curve.

Abstract: Example implementations relate to swath height error compensation. Some examples may determine a density of an image to be printed in an overlap area of a printing material. The overlap area may include target pixels capable of being printed by a first set of drop ejection elements and a second set of drop ejection elements that are redundant to the first set of drop ejection elements. Some implementations may also determine a mask to apply to the first and second set of drop ejection elements based on the determined density, and the mask may designate at least one additional drop to apply to at least one target pixel in the overlap area by at least one of the first and second set of drop ejection elements. Some implementations may also apply the mask to the first set of drop ejection elements and the second set of drop ejection elements.

Abstract: Example implementations relate to swath height error compensation. Some examples may determine a density of an image to be printed in an overlap area of a printing material. The overlap area may include target pixels capable of being printed by a first set of drop ejection elements and a second set of drop ejection elements that are redundant to the first set of drop ejection elements. Some implementations may also determine a mask to apply to the first and second set of drop ejection elements based on the determined density, and the mask may designate at least one additional drop to apply to at least one target pixel in the overlap area by at least one of the first and second set of drop ejection elements. Some implementations may also apply the mask to the first set of drop ejection elements and the second set of drop ejection elements.

Abstract: Certain methods and systems are described to provide color modelling. This color modelling applies to halftone images. In one example, a correction parameter for a color model is determined by minimizing a distance metric between a set of estimated spectral reflectance values and a set of measured spectral reflectance values to generate a multi-dimensional correction parameter. This enables a color model to be used to map at least one Neugebauer Primary area coverage value to at least one spectral reflectance value.