Fingerprint analysis involves the examination of friction ridge impressions which takes into account substrate, matrix, development medium, pressure distortion markers and so on [4].  In addition, the examiner interprets friction ridge feature shapes in position and assesses the  clarity and reliability of each.  The examiner makes a best estimate of its aggregate weight or value based on subjective and/or empirical probability modeling.  Finally, based on the relevant population for the case at hand, the examiner predicts whether or not the total value or T-Value for the arrangement of ridge features is "usable" for purposes of comparison and subsequent identification or exclusion.

When friction ridge detail is first analyzed, the examiner’s documentation should be such that another qualified examiner can determine what was done, if needed (see Bench Notes).

Latent Prints

Friction ridge analysis of a latent print for purposes of identification should be completed prior to comparison.  At a minimum, the examiner should determine the following:

• Relevant population group for the case at hand, e.g., conservative upper-bound plausible number of people who could have committed the crime at hand (e.g., local population, county AFIS database, state AFIS database, national AFIS database, etc.).
• Total ridge feature types in position, e.g., 1 clear, reliable ending ridge unit in a funnel with 2 intervening ridge counts to nearest neighbor, 1 clear, unreliable dot with 4 intervening ridge to nearest neighbor, etc.
• Total quantitative-qualitative value, e.g. T-Value, for the aggregate amount of ridge features.
• If the T-Value is sufficient to infer positive identification based on relevant population for the case at hand.

Known Prints

Friction ridge analysis of a known print begins after it has been determined that the latent print is usable for purposes of identification.  Similar to the analysis of a latent print, at a minimum, the examiner should determine the following for the known print:

• Total ridge feature types in position, e.g., 1 clear, reliable ending ridge unit in a funnel with 2 intervening ridge counts to nearest neighbor, 1 clear, unreliable dot with 4 intervening ridge to nearest neighbor, etc.
• Total quantitative-qualitative value, e.g. T-Value, for the aggregate amount of ridge features.
• If the T-Value is sufficient to infer positive identification based on relevant population for the case at hand.

Fingerprint Analysis During Routine Casework

For purposes of a timely work product during the course of routine casework, a minimum T-Value, which is based on the FBI default population standard of 300 million people (total population of the United States) used to calculate and match DNA profiles, of 66 billion may be used to infer sufficiency to establish positive identification with a reasonable degree of scientific certainty.

It is significant to note that a T-Value of 66 billion is exceeded when any clear, reliable eleven (11) Level II ridge formations in a latent impression found in excellent agreement to an exemplar and consequently may be used to establish valid basis for sufficiency to identify.  Since the least weighted Level II ridge formation type is the diminishing area ending ridge, eleven (11) of these represent a T-Value 100 billion which exceeds that for the largest and best look-alike ever recorded (see Chesapeake IAFIS Non-Match) as well as the above 66 billion T-Value threshold. 

However, when the case at hand clearly indicates a smaller relevant population should be used or when the importance of the case demands that the number of people who could have plausibly committed the crime can be defined, then the above T-Value threshold should be refined accordingly (see Pre-Determined Minimum to Individualize).

Example

Based on a crime that occurs on a boat in which the fingerprint population is defined as 4,500 (equivalent to only 450 possible suspects) do the below amounts of ridge detail have sufficient weight to establish valid basis for sufficiency to individualize (see below images)?

Fingerprint examiner opinion will greatly differ based on the subjective nature of the problem.  However, the T-Model can precisely define which amounts in the below images have a sufficient amount of ridge features necessary for comparison, and if presented with a similar amount of corresponding ridge formations in another impression, can be used to infer positive identification based on the given population group and the subsequent defined T-Value.

Based on Level II ridges only and a relevant fingerprint population of 4,500, which of the following images display sufficient ridge detail for purposes of identification?  

Image 1 

9 ending ridges and 2 dots 

Image 2 

 5 ending ridges and 2 dots

 Image 3

 3 ending ridges and 2 dots

 Image 4

2 ending ridges and 2 dots

Image 5

1 ending ridge and 2 dots

Image 6

1 ending ridge and 1 dot

 Image 7 

1 ending ridge 

The interpretation of ridge unit quantitative weight and assessment of ridge unit quality should speak for itself and allow for demonstration, even to the layman.

The total value or "T-Value" for an aggregate amount of friction ridge features is defined by multiplying the quantitative and qualitative values for each to each other.  The product of these values equals the total value for the arrangement of friction ridge features.  The reciprocal of the T-Value equals the fingerprint match probability.  They are the same.