Abstract
This paper presents an artificial intelligence approach towards classification of persons based on verbal descriptions of their facial features. Frame knowledge representation, fuzzy sets, fuzzy IF-THEN rules, and fuzzy granulation are employed. Features of face elements (nose, eyes, etc.) are extracted by use of existing detection techniques, such as measurements of horizontal and vertical sizes. Linguistic variables that correspond to fuzzy sets, representing selected facial features, are applied in the frames and fuzzy rules. Linguistic values defined by the fuzzy sets conform the terminology applied by law enforcement to create an eyewitness verbal description. Classification results are illustrated in three cases of the system’s input: facial composites (sketches) created by an artist, images (digital pictures) from a face database, and verbal descriptions.
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Kurach, D., Rutkowska, D., Rakus-Andersson, E. (2014). Face Classification Based on Linguistic Description of Facial Features. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2014. Lecture Notes in Computer Science(), vol 8468. Springer, Cham. https://doi.org/10.1007/978-3-319-07176-3_14
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DOI: https://doi.org/10.1007/978-3-319-07176-3_14
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