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Excerpt from Computer Design April 1992 FUZZY MUG SEARCH HELPS COPS CATCH CROOKS ---------------------------------------Well known to all devotees of detective shows is the scene where a crime victim sits for long hours paging through mug books to try to identify some evildoer. Even when police departments have managed to computerize their databases of known perpetrators, the process of narrowing the identification search to a manageable number of mug shots based on a witness's description is a tedious one. Knowledge Based Systems of White Plains, NY added a fuzzy front end to the image database of a major European police department that significantly reduced the number of look throughs witnesses had to do before finding a set of pictures they could seriously work with to try to identify a subject. In the past, if someone came in and said, ``He was kind of tall and heavy-set and looked rather young,'' the police would have only a vague idea of what group of pictures to start showing the witness. Even if the system were computerized, someone would have to decide where the cutoff point was for ``rather young,'' or ``tall.'' If a person were described at 6'1'' but was really 5'11'', the system might not catch the out of range number even if other factors in the description pointed to an overall match. In addition to implementing a front end to the database that uses fuzzy sets to describe characteristics like ``old,'' ``thin,'' ``tall'' and so on, KBS built in what it calls ``perspective shifting'' and ``semantic plies.'' Perspective shifting changes the shape of the fuzzy set representing, say, ``tall'' if the witness is for instance a 16-year-old girl or Japanese. It allows the system to search for ``old'' from a ``young'' perspective. Semantic plies adjust the description as in ``tall for women'' or ``heavy for Samoans.'' The success of searching for a useful set of mug shots to examine is because perspective shifting and semantic plies affect the degree of belief in a fuzzy concept based on the witness's characteristics; they do not make crisp distinctions. Thus 5 feet will have a greater degree of membership in ``tall' for a 10-year-old than for an adult, etc. The pictures of subjects to look at are selected on an overall degree of truth from the combined described characteristics, which in this instance was set at 0.38. According to KBS, the old system required an average of 16 look-throughs to find a set that someone could actually work with, while the fuzzy system reduced the number of look-throughs to two. -----------------------------------------------------------This is article is provided with permission from Computer Design. For subscription information to Computer Design, call Paul Westervelt at (913) 835-3161. Do not redistribute in an form (written or electronic) without permission from Computer Design.

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