Abstract: In some examples, an imaging device can include a processing resource and a memory resource storing instructions to cause the processing resource to perform a feature extraction process to extract a gamut-based feature included in a plurality of pixels of a scanned image to determine whether the scanned image includes a particular marking, apply a classification model to the scanned image, and optimize the scanned image based on the classification of the scanned image.

Abstract: In some examples, an imaging device can include a processing resource and a memory resource storing instructions to cause the processing resource to perform a feature extraction process to extract a gamut-based feature included in a plurality of pixels of a scanned image to determine whether the scanned image includes a particular marking, apply a classification model to the scanned image, and optimize the scanned image based on the classification of the scanned image.

Abstract: A system generates a prediction model for makeup color matching. The system includes a data storage device and a modeling engine. The data storage device stores a plurality of color sets comprising a skin color set, a makeup color set, and a target color set. The modeling engine is coupled to the data storage device and configured to generate a prediction model and an output color set. The prediction model models generation of the target color set based on inputs from the skin color set and the makeup color set. The output color set approximates the target color set with a predictable accuracy.

Abstract: A system generates a prediction model for makeup color matching. The system includes a data storage device and a modeling engine. The data storage device stores a plurality of color sets comprising a skin color set, a makeup color set, and a target color set. The modeling engine is coupled to the data storage device and configured to generate a prediction model and an output color set. The prediction model models generation of the target color set based on inputs from the skin color set and the makeup color set. The output color set approximates the target color set with a predictable accuracy.

Abstract: A system generates a prediction model for makeup color matching. The system includes a data storage device and a modeling engine. The data storage device stores a plurality of color sets comprising a skin color set, a makeup color set, and a target color set. The modeling engine is coupled to the data storage device and configured to generate a prediction model and an output color set. The prediction model models generation of the target color set based on inputs from the skin color set and the makeup color set. The output color set approximates the target color set with a predictable accuracy.

Abstract: A system generates a prediction model for makeup color matching. The system includes a data storage device and a modeling engine. The data storage device stores a plurality of color sets comprising a skin color set, a makeup color set, and a target color set. The modeling engine is coupled to the data storage device and configured to generate a prediction model and an output color set. The prediction model models generation of the target color set based on inputs from the skin color set and the makeup color set. The output color set approximates the target color set with a predictable accuracy.

Abstract: In some examples, an imaging device may include a controller including processing circuitry to detect, a first quantity of rows of pixels to be included as a first band of a contone image, process the pixels of each row of the first band in parallel raster order, detect a second quantity of rows of pixels to be included as a second band of the contone image; and process the pixels of each row of the second band in response to the completion of the pixels of the first band, where the rows of the second band are processed in parallel in serpentine order with respect to the first band.