UC Riverside

Seam carving is an algorithm that analyzes image content and can be used for size reduction in a manner that avoids direct compression or downscaling. Seam carving iteratively identifies horizontal and/or vertical paths of least visual importance and removes them from the image; each path removal reduces the length or width of the image by one row or column of pixels. This article adapts seam carving to reduce excess area of flow-based microfluidic chips that have been drawn by hand or by computer-aided heuristics without negatively impacting their functionality. The proposed approach leverages domain knowledge, wherein the image to be carved consists of I/O ports, components, and fluid channels, with known and understood fluidic behavior. Three different variants of seam carving are presented: 1) linear; 2) nonlinear; and 3) nonrectilinear; experimental results show that nonrectilinear, which is the most general of the three, yields the best results: it improves area utilization by 8.6\times and reduces fluid routing channel length by 73% across a set of benchmark microfluidic designs.