Non-Fiction Books:

Fingerprints

Analysis and Understanding
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Description

The unique composition of the skin on the inner hands and bottom of the feet affords not only a utilitarian benefit in providing friction but also provides a forensic marker for identifying individuals. Fingerprints: Analysis and Understanding is the most fundamental, up-to-date resource available on the techniques of obtaining and analyzing latent fingerprint evidence. Using an outline format for rapid comprehension, this concise text is as easy to understand by those collecting evidence as it is by those in the branches of criminal justice who need to understand the principles. Divided into two parts, the book begins with the basics of analysis, providing a brief history, systematic methods of identification, fingerprint pattern types and their associated terminologies, and current classifications. The second section covers the identification and presentation of evidence in the courtroom, demonstrating both the traditional, manual method of lifting prints and the newer techniques for automated and live scans. The book provides instruction on searching and developing latent prints, storage, and comparison of prints. Author Mark R. Hawthorne is the lead instructor in physical evidence and crime scenes at the San Francisco Police Regional Training Academy. He brings his twenty-nine years experience in police work processing over 3000 crime scenes to present a practical, concise guide to a complex science, helping readers to understand the principles, applications, and uses of fingerprints, whether at the scene, or in the courtroom.

Author Biography

San Francisco Police Department, California, USA (Retired)
Release date NZ
November 26th, 2008
Audience
  • Professional & Vocational
Country of Publication
United States
Illustrations
32-page section w/ page numbers in CMYK; 1 Tables, black and white; 69 Illustrations, black and white
Imprint
CRC Press Inc
Pages
142
Publisher
Taylor & Francis Inc
Dimensions
156x234x8
ISBN-13
9781420068641
Product ID
2717581

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