Abstract: Examples disclosed herein relate to receiving a query from a user associated with a requested digital element, determining whether the query comprises an attribute associated with the requested digital element, identifying at least one digital element comprising the attribute, determining whether a the requested digital element can be identified from the at least one digital element, and performing an action on the requested digital element according to the query.

Abstract: In an example, a capture system includes a content capture mechanism, an isolation engine, a mark strength engine, and a parameter controller. In that example, the isolation engine generates mark data, the mark strength engine identifies a first variance level in a first region of a first set of mark data, and the parameter controller adjusts a parameter of the content capture mechanism in accordance with a strength change based on a comparison of the first variance level to a second variance level in a first region of a second set of mark data.

Abstract: In one implementation, a system for providing mark triggered content recommendations include a data engine to receive a scanned image ID of a first mark with a corresponding location of the first mark, a location engine to determine a location of a second mark within a radius of the corresponding location of the first mark, and a content engine to provide content associated with the first mark and a recommendation of content associated with the second mark.

Abstract: In an example, a capture system includes a content capture mechanism, an isolation engine, a mark strength engine, and a parameter controller. In that example, the isolation engine generates mark data, the mark strength engine identifies a first variance level in a first region of a first set of mark data, and the parameter controller adjusts a parameter of the content capture mechanism in accordance with a strength change based on a comparison of the first variance level to a second variance level in a first region of a second set of mark data.

Abstract: In one example, a system including an isolation engine, a normalization engine, and a channel engine is described. In the example, the isolation engine generates mark data using a mark technique based on a first input color channel and a second input color channel, the normalization engine scales intensity values of a set of pixels of the mark data to a greater range, and the channel engine generates output channel data for a plurality of output color channels from normalized mark data based on the scaled intensity values.

Abstract: In one example, a system including an isolation engine, a normalization engine, and a channel engine is described. In the example, the isolation engine generates mark data using a mark technique based on a first input color channel and a second input color channel, the normalization engine scales intensity values of a set of pixels of the mark data to a greater range, and the channel engine generates output channel data for a plurality of output color channels from normalized mark data based on the scaled intensity values.