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A computerized neural network method for pattern recognition of cocaine signatures

J F Casale1, J W Watterson

  • 1DEA Special Testing, McLean, VA.

Journal of Forensic Sciences
|March 1, 1993
PubMed
Summary

This study introduces a new method for searching cocaine signature databases using artificial intelligence. The developed software helps forensic experts quickly identify similar cocaine samples, aiding investigations.

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Area of Science:

  • Forensic Science
  • Artificial Intelligence
  • Pattern Recognition

Background:

  • Cocaine signature analysis is crucial for drug investigations.
  • Existing methods for searching large databases can be time-consuming.
  • The need for efficient tools to link seized drug samples is high.

Purpose of the Study:

  • To develop a rapid procedure for searching large cocaine signature databases.
  • To utilize pattern recognition for identifying similar cocaine signatures.
  • To support forensic experts in batch origin determination.

Main Methods:

  • Implementation of a multilayer perceptron neural network for pattern recognition.
  • Development of a personal computer (PC)-based software for database searching.

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  • Utilizing a large database of cocaine signatures for analysis.

    • Main Results:

    • The software enables rapid identification of closely resembling cocaine signatures.
    • The system is currently in daily use at the North Carolina State Bureau of Investigation (NCSBI).
    • Generated intelligence reports assist in building drug-related conspiracy cases.

    Conclusions:

    • The developed software provides an effective tool for forensic cocaine signature analysis.
    • The use of neural networks enhances the speed and accuracy of database searches.
    • This technology aids law enforcement in field investigations and case building.