Abstract: An example non-transitory machine-readable medium includes instructions that, when executed by a processor, cause the processor to define a color encoding based on selected colors within a reference color space. The selected colors include white, black, and a set of chromatic colors spanning different print gamuts of a range of different printing devices. The instructions are further to encode a source datapoint of a source color space with the color encoding to obtain a reference datapoint of the reference color space by determining the reference datapoint as a mixture of white, black, and two colors selected from the set of chromatic colors, and output the reference datapoint.

Abstract: Example printing devices and methods of the printing devices are disclosed. Target data is received responsive to imaging the source item. The source item includes a mark indicative of rendering information. The target data is used to detect the rendering information. The target object is output based on the target data and the rendering information.

Abstract: Example printing devices and methods of the printing devices are disclosed. Target data is received responsive to imaging the source item. The source item includes a mark indicative of rendering information. The target data is used to detect the rendering information. The target object is output based on the target data and the rendering information.

Abstract: An example computer-readable medium storing machine-readable instructions that, when executed by a processor, cause the processor to receive an image, identify a first color region in the image, the first color region having a color level below a color level threshold, and fortify the first color region.

Abstract: In an example, a method includes receiving a data model of an object to be generated in additive manufacturing, the data model comprising geometric object data describing the object and property data. A property affecting object generation parameter may be determined for the object and a modified data model of the object may be derived by applying a transformation to the property data associated with the property affecting object generation parameter, wherein the transformation is to compensate for a property value shift associated with the property affecting object generation parameter.

Abstract: In an example, a method includes determining an additive manufacturing process instruction, the additive manufacturing process instruction comprising an instruction specifying a coverage of a set of print agents comprising a fusing agent and a colorant to be applied to build material. A color and a behavioural property of carrying out an additive manufacturing process according to the additive manufacturing process instruction may be determined and, in response to a determination that the behavioural property meets predetermined parameters, the instruction and the color may be added to a color mapping resource.

Abstract: A computing system can include a preview module and a display interface. In some examples, the preview module can obtain adjustment values for adjusting an operation for a printer to achieve or form an output of the printer with a set of attributes included in a print job. Additionally, the preview module can generate a preview of the output, based on the adjustment values, the set of attributes and a set of configuration parameters of the display component. In such examples, the preview can be based on the adjustment values, the set of attributes and a set of configuration parameters of the display component. In some examples, the preview module can communicate the preview of the output to a display component using the display interface.

Abstract: A technique includes acquiring data representing a first image produced by electronically scanning a page against a background. The first image contains a non-uniform background content due at least in part to a variation introduced by the background being non-uniform. The technique includes extracting an image of the page from the first image, wherein the extraction includes characterizing the background content of the first image; identifying candidate pixels associated with the page based at least in part on the characterized background content; and based at least in part on the identified candidate pixels and a model for a boundary of the page, determining the boundary of the page.

Abstract: A technique includes acquiring data representing a first image produced by electronically scanning a page against a background. The first image contains a non-uniform background content due at least in part to a variation introduced by the background being non-uniform. The technique includes extracting an image of the page from the first image, wherein the extraction includes characterizing the background content of the first image; identifying candidate pixels associated with the page based at least in part on the characterized background content; and based at least in part on the identified candidate pixels and a model for a boundary of the page, determining the boundary of the page.

Abstract: A host server receives a content request in the form of a Uniform Resource Identifier (URI) from a client. The URI identifies a first content resource and describes a first service resource to be applied to a representation of the first content resource. The URI is translated into an instruction set. The host server causes execution of the instruction set to apply the first service resource to a representation of the content resource. A processed representation of the first content resource is then provided to the client in response to the request.

Abstract: A host server receives a content request in the form of a Uniform Resource Identifier (URI) from a client. The URI identifies a first content resource and describes a first service resource to be applied to a representation of the first content resource. The URI is translated into an instruction set. The host server causes execution of the instruction set to apply the first service resource to a representation of the content resource. A processed representation of the first content resource is then provided to the client in response to the request.

Abstract: Computer software for and a method of calculating ring-wedge data from a digital image by performing a discrete Fourier transform of the digital image. A discrete autocorrelation, discrete cosine transform, and/or Hadamard transform is also preferably performed, together with providing the results to a neural network (most preferably a fully connected, three-layer, feed-forward neural network with sigmoidal activation functions) to perform pattern recognition on the data.