查看文章

In computational forensics, it has become essential to find similarity between some of the uncertain information found in crime scene and in the criminal records. Quite often, the information acquired such as facial features from on-lookers, other information like finger prints, shoe prints from Crime Scene Investigation (CSI) are vague and uncertain. In such situations, decision making with uncertain information as such may go erroneous. Therefore, we propose a novel approach of fsimilarity in identifying fuzzy patterns including fuzzy faces, to estimate each of the features in faces, fingerprints, weapons in terms of membership values. The multiple membership values from different features are subjected to OWA operators for decision making. In this direction, we begin our work implementing f-similarity in f-geometric objects like f-rectangle, fsquare and f-circle using f-theorem. The outputs are justified with extent of fuzziness in f-objects.