  We consider the irregular strip packing problem of rasterized shapes, where a
given set of pieces of irregular shapes represented in pixels should be placed
into a rectangular container without overlap. The rasterized shapes provide
simple procedures of the intersection test without any exceptional handling due
to geometric issues, while they often require much memory and computational
effort in high-resolution. To reduce the complexity of rasterized shapes, we
propose a pair of scanlines representation called the double scanline
representation that merges consecutive pixels in each row and column into
strips with unit width, respectively. Based on this, we develop coordinate
descent heuristics for the raster model that repeat a line search in the
horizontal and vertical directions alternately, where we also introduce a
corner detection technique used in computer vision to reduce the search space.
Computational results for test instances show that the proposed algorithm
obtains sufficiently dense layouts of rasterized shapes in high-resolution
within a reasonable computation time.
