Image object adaptation in variable data printing

摘要

In variable data printing (VDP), it is desirable to automatically fit an arbitrary shaped image object into an arbitrarily shaped copy hole in a template with maximized use of the available space. In this paper, we describe a practical image processing method that segments out the object and determines the scale and translation factors for the optimal fitting. For our application, an image object is placed on a uniformed color background in a JPEG compressed image file. The compression artifacts around the object boundary area complicate object segmentation. In order to identify object boundary precisely, we developed an orientation-dependent adaptive region growing method, which significantly improve the boundary accuracy. In the first step, we identify the background pixels using zero thresholding. Connectivity analysis is then performed to remove very small blobs. Mathematical morphological operations are applied to background pixels in order to smooth the border. In the second step, object boundaries are refined using the proposed orientation-dependent adaptive region growing. In determining the optimal scale and translation, we use an image-based exhaustive search algorithm that steps through a set of scaling factors in descending order until a complete fit is found. The exit scaling factor along with the associated mass center of the feasible translations are then used for the object placement.