Extracting Masks from Optical Images of VLSI Circuits

This paper explores line labeling algorithms for extracting the mask layers from a clean line drawing representing the optical image of a VLSI chip. We start by developing a suitable world model for VLSI images, treating a chip as a multilayer sandwich of translucent layers, each of which is composed of planar and rectilinear strips. The arrangement of these strips is interpreted according to a hierarchical description of the chip in which strips combine to form electrical elements, which in turn form gates, which in tum form even higher-level building blocks. We model the optical image of the VLSI chip as a simple 2-D projection of these layers, in which all strip boundaries are preserved but all depth and layer identification is lost. We assume that this image is a perfect line drawing of the chip. Our vision problem is to reverse the image-formation process in order to reconstruct the original scene and extract the original masks. To recover this information, we show that features and design constraints on the layers translate into a natural labeling scheme for the lines, junctions, and regions defined by the line drawing. We present two different algorithms for extracting masks. The first uses a constraint propagation algorithm, exploiting the natural constraints on the junctions to reduce the set of possible interpretations of the lines. The second algorithm attaches a series of labels to the image, building up path fragments from lines, then linking them into paths, assigning paths to layers, labeling the layers, and assigning insides and outsides within each layer. The key issue is to use as much knowledge as possible about VLSI, together with hints from the operator, to reduce the ambiguity of the line drawing, and thereby reduce the number of sets of masks that could possibly form the image. Performance of the system is shown on a typical CMOS gate. We conclude by showing how our approach can be used to generalize previous line drawing interpretation methods for projected images of 3-D trihedral blocks worlds with both opaque and transparent surfaces.