Advances in Computer Science and Information Technology. Computer Science and Information Technology. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part III

Research Article

Fuzzy Identification of Geometric Shapes

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  • @INPROCEEDINGS{10.1007/978-3-642-27317-9_28,
        author={B. Imran and M. Beg},
        title={Fuzzy Identification of Geometric Shapes},
        proceedings={Advances in Computer Science and Information Technology. Computer Science and Information Technology. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part III},
        proceedings_a={CCSIT PART  III},
        year={2012},
        month={11},
        keywords={
                    -geometry 
                    -similarity fuzzy identification 
                    -patterns fuzzy geometry},
        doi={10.1007/978-3-642-27317-9_28}
    }
    
  • B. Imran
    M. Beg
    Year: 2012
    Fuzzy Identification of Geometric Shapes
    CCSIT PART III
    Springer
    DOI: 10.1007/978-3-642-27317-9_28
B. Imran1,*, M. Beg1,*
  • 1: Jamia Millia Islamia (A Central University)
*Contact email: imran.fuz@gmail.com, mbeg@jmi.ac.in

Abstract

The identification of criminals with sketches can no longer sustain using conventional image processing techniques. Since, it behaves mechanistically, that is, a system which behaves as per given set of rules. We propose a humanistic system for identification of sketches of criminals. Certainly, one must be looking forward for a novel approach, which identifies similarity between a photographic image and a transformed fuzzy image i.e., a sketched image. The transformation on images could be anyone among rotation, reflection, translation, scaling or shearing. In this regard, our approach identifies fuzzy geometric shapes, like humans identify any imprecise shape with their cognition. Such fuzzy shapes cannot be left unidentified under crucial conditions. We begin with estimation of f-validity and then the f-similarity for f-geometric objects, which are considered as basics for developing a humanistic identification system. We implement OWA operators for computing f-similarity in fuzzy geometric shapes. Moreover, the results are found to be justified with the extent of fuzziness.