The deviation of micromachined products from their intended design poses a significant challenge for designers. To address this issue, numerical simulations can be employed for predicting such deviations. In this research paper, we present a methodology aimed at preserving accuracy in micromachining products resulting from topology optimization, particularly when intricate geometric features are involved. The accuracy of final products can be difficult to achieve due to the inherent limitations of microfabrication processes, specifically in lithography and etching. To overcome these limitations, our proposed methodology combines density filters and morphological operators to generate lithography masks that closely align with the surface of micromachined silicon. We have validated the efficacy of this methodology by selecting a benchmark problem focused on maximizing the stiffness of a cantilever beam across various volume fractions. The results demonstrate a significant improvement in accuracy while maintaining adherence to the desired design specifications. Additionally, we have conducted simulations of surface micromachining with photolithography to further substantiate the effectiveness of our proposed method in achieving enhanced accuracy for optimized topological structures. These findings hold practical implications for the design of Micro Electronic Mechanical Systems (MEMS) and other similar applications where accuracy is of paramount importance. By providing a means to compensate for the limitations inherent in microfabrication processes, our proposed methodology can contribute to the production of highly accurate and topologically optimized products.