FINGERPRINT IDENTIFICATION FOR FORENSIC CRIME SCENE INVESTIGATION

FINGERPRINT IDENTIFICATION FOR FORENSIC CRIME SCENE INVESTIGATION

ABSTRACT

Fingerprints are the most widely used biometric feature for person identification and verification in the field of biometric identification. This study presents the implementation of a minutiae based approach to fingerprint identification and verification of the fingerprint image captured at the crime scene. Digital evidence enhancement techniques, such as Fast Fourier Transform and Image Subtraction, have been described in detail.

CHAPTER ONE

INTRODUCTION

The evidence photographer is faced with a wide range of photographic challenges at crime scenes. Recording crucial evidence in the form of fingerprints, shoeprints, or other impressions is often problematic. These images may be extremely fragile as well as difficult to see. The background color or texture can easily overpower subtle detail. Curved, specular, or uneven surfaces may resist attempts to record all of the detail in one exposure. Lastly, exhibits bearing evidence can often be difficult or impossible to remove from the scene for photography in a controlled environment, without risking damage to the evidence. In most circumstances, conventional photographic procedures are used successfully to record such evidence discovered at crime scenes. The experienced photographer may employ oblique, tent or coaxial lighting, tilt and swing camera movements, or polarizing and contrast filters to obtain a suitable recording. Evidence at a crime scene is that the evidence is often masked behind backgrounds [1]. This makes it difficult for extracting key components from the evidence. Often times, the background color of the crime scene can overpower the faint detail of the evidence. Types of evidence that this can occur on is with finger prints and shoe prints at the crime scene. To correct this problem, image enhancement techniques can be used to obtain the relevant information that is needed for the investigators. The system was developed using C#.NET. Providing all the necessary tools for designing and testing different filtering techniques.

TOPIC: FINGERPRINT IDENTIFICATION FOR FORENSIC CRIME SCENE INVESTIGATION

Format: MS Word

Chapters: 1 - 5
Delivery: Email

Number of Pages: 65

Price: 3000 NGN

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