                       Excerpt from Computer Design
                                April 1992
                 FUZZY MUG SEARCH HELPS COPS CATCH CROOKS
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     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.
     

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