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study and understanding of handwriting later came to play an important role in forensic science and criminal justice Early practitioners developed manual (observation-based) techniques to analyze and match handwriting samples for the purpose of case evidence Automated handwriting signature verification systems evolved from implementations of more general character and gesture recognition technologies developed in the companion field of machine vision and Human Computer Interfaces (HCI) in the late 1970s and early 1980s HCI designers sought to recognize static characters, numerals, symbols, and gestures from electronic handwriting traces so they could interpret the inputs as text strings, graphical elements, or application commands Machine vision researchers developed working methods for achieving this goal on static inputs by 1977 (Ali and Pavlidis 1977, 537-541) Signature recognition systems became the next logical challenge for pen computing, and with the availability of the force-sensitive capture techniques, prototype systems were soon realized.

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Many patents have been issued related to the capture and processing of handwriting Notably, in 1977, a patent for Personal identification apparatus was awarded to Veripen, Inc, of New York, for an apparatus to acquire pressure information1 That same year Veripen, Inc, was involved in biometrics testing that assessed the use of early automatic handwriting verification and speaker verification That testing was conducted by The MITRE Corporation and was done on behalf of the Electronic Systems Division of the United States Air Force2 Today, 25 years later, computer techniques to process characters and gestures automatically are quite robust and well developed (Hand-written character recognition was in fact a critical capability for the success of the Palm Pilot and Win CE stylus-based personal digital assistants.

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) Although highly cursive text is still not fully machine-readable, a number of good implementations of dynamic signature verification techniques are commercially available As with most biometrics, the implementations are not based on any standard prescribed features; thus performance and particular match results will differ to some extent across different vendor solutions..

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As explained in 1, if your program includes frequent references to the members of a namespace, having to specify the namespace each time you need to refer to one quickly becomes tedious. The using directive alleviates this problem. Throughout this book, you have been using using to bring the System namespace into view, so you are already familiar with it. As you would expect, using can also be used to bring namespaces that you create into view. There are two forms of the using directive. The first is shown here: using name;

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