The need of finding a way to design a company trademark, without the worry of possible infringement on the intellectual property rights, has become exceedingly important as the economy and the accompanying intellectual property concerns advanced greatly in recent years. Traditionally, registered trademarks are stored in image databases and are categorized and retrieved by descriptions and keywords given by human workers. This is extremely time-consuming and considered by many as inappropriate. In this work we focus on image feature and content related techniques, or content-based image retrieval (CBIR) methods. Nevertheless, we still need human inputs since by law the most crucial basis for discerning the similarity or difference of two trademarks has to rely on human¡¦s naked eye. Therefore in this work we created a program which incorporates an man-machine interface allowing users to input various weighting factors each emphasizing a specific feature or shape of the trademark. The Zernike moments, and some new image compactness indices are used in the computations for image comparisons.