A method for processing data to adapt image data to produce a visual asset including an image of an object, the method comprising: obtaining a digital image; storing first data that represents a reference connectivity graph of a marker to be recognized in the digital image that comprises at least one light sampling point and at least one dark sampling point, wherein the reference connectivity graph is any association of arcs that are connected at nodes to form a plurality of enclosed regions, wherein the at least one light sampling point is an unprinted area or an area printed with light colors, and wherein the at least one dark sampling point is a full printed area of the reference connectivity graph; generating second data that represents a candidate connectivity graph by analyzing the digital image, wherein the candidate connectivity graph comprises any association of arcs that are connected at nodes to form a plurality of enclosed regions defined by the digital image; comparing the candidate connectivity graph with the reference connectivity graph to determine whether the candidate connectivity graph matches the reference connectivity graph; in response to determining that the candidate connectivity graph matches the reference connectivity graph, generating third data comprising a marker transform that at least maps nodes of the reference connectivity graph to nodes of the candidate connectivity graph; analyzing the digital image to detect one or more light sampling points and one or more dark sampling points using the marker transform; sampling at least one pixel value at at least one equivalent light sampling point in the digital image to determine a baseline white value for the digital image; sampling at least one pixel value at at least one equivalent dark sampling point in the digital image to determine a black point for the digital image; determining one or more luminance values for the one or more light sampling points detected in the digital image; determining one or more luminance values for the one or more dark sampling points detected in the digital image; based on the one or more luminance values for the one or more light sampling points and the one or more luminance values for the one or more dark sampling points, determining a lighting gradient that exists between said sampling points within the digital image depicting at least the marker; and building a visual asset that visualizes the object in the digital image using at least the third data, the baseline white value and the black point by modifying luminance of the visual asset to match the lighting gradient to simulate lighting in environment in which the digital image was obtained. obtaining a digital image; storing first data that represents a reference connectivity graph of a marker to be recognized in the digital image that comprises at least one light sampling point and at least one dark sampling point, wherein the reference connectivity graph is any association of arcs that are connected at nodes to form a plurality of enclosed regions, wherein the at least one light sampling point is an unprinted area or an area printed with light colors, and wherein the at least one dark sampling point is a full printed area of the reference connectivity graph; generating second data that represents a candidate connectivity graph by analyzing the digital image, wherein the candidate connectivity graph comprises any association of arcs that are connected at nodes to form a plurality of enclosed regions defined by the digital image; comparing the candidate connectivity graph with the reference connectivity graph to determine whether the candidate connectivity graph matches the reference connectivity graph; in response to determining that the candidate connectivity graph matches the reference connectivity graph, generating third data comprising a marker transform that at least maps nodes of the reference connectivity graph to nodes of the candidate connectivity graph; analyzing the digital image to detect one or more light sampling points and one or more dark sampling points using the marker transform; sampling at least one pixel value at at least one equivalent light sampling point in the digital image to determine a baseline white value for the digital image; sampling at least one pixel value at at least one equivalent dark sampling point in the digital image to determine a black point for the digital image; determining one or more luminance values for the one or more light sampling points detected in the digital image; determining one or more luminance values for the one or more dark sampling points detected in the digital image; based on the one or more luminance values for the one or more light sampling points and the one or more luminance values for the one or more dark sampling points, determining a lighting gradient that exists between said sampling points within the digital image depicting at least the marker; and building a visual asset that visualizes the object in the digital image using at least the third data, the baseline white value and the black point by modifying luminance of the visual asset to match the lighting gradient to simulate lighting in environment in which the digital image was obtained.