In modern photolithography, optical proximity correction (OPC) has been widely adopted to improve the image fidelity of the mask on silicon wafer and, hence, improve the yield and the performance of integrated circuits. In recent years, model based optical proximity correction (MBOPC) has evolved from a nice-to-have feature to a must-have feature, especially, for the advanced nodes, 90 nm and beyond. The purpose of MBOPC is to adjust the designed pattern on the photomask to introduce mask perturbations, such that the layout printed on the wafer is as close as possible to the drawn layout. Before MBOPC is conducted on the full chip, a high quality and yet compact OPC model must be built, which simulates the photolithography process accurately. A high quality OPC model apparently relies on the quality of the empirical critical-dimension data in terms of both metrology noisiness and layout representativeness. Although more measurements on a large number of patterns will keep overall noise at lower levels and provide better input to OPC modeling, it is crucial to choose the representative patterns wisely and minimize the redundancy of gauges due to the limited metrology budget and the requirement of shortening turnaround time. In this article, the authors propose a method that checks the linear response of the optical signal on the one-dimensional (1D) patterns and selects the most representative patterns among all possible 1D structures. (C) 2010 American Vacuum Society. [DOI: 10.1116/1.3511510]