Two Approaches for Mobile Phone Image Insignia Identification Nitin Mishra and Sunil Kumar Kopparapu Abstract Insignia identification is an important task especially as a self help appli- cation on mobile phones which can be used in museums. We propose a knowledge driven rule-based approach and a learning based approach using artificial neural network (ANN) for insignia recognition. Both the approaches are based on a common set of insignia image segmentation followed by extraction of simple, yet effective features. The features used are based on one of frugal processing and computing to suit the mobile computing power. In both the approaches we identify each extracted segment in the insignia; the correct recognition of the segment followed by post processing results in the identification of the insignia. Experimental results show that both approaches work equally well in terms of recognition accuracy of over 90% in terms of identification of the segments and 100% in terms of the actual insignia identification. 1 Introduction Visit to a museum often requires a guide who can describe the details associated with an artifact on display. There are problems understanding the artifacts especially if the visitor is from a different country and speaking a different language. A handy mobile device that can capture the image of the artifact on display and then show details of the artifact, in the visitors own language is an usable solution. This does not only make the experience of the visitor to the museum satisfying, but also provides him the chance to see in detail the information about what he wants to see rather than depend on a human guide available at the museum. Nitin Mishra TCS Innovation Labs - Delhi, INDIA e-mail: Mishra.Nitin@TCS.Com Sunil Kumar Kopparapu TCS Innovation Labs - Mumbai, INDIA e-mail: SunilKumar.Kopparapu@TCS.Com 1