SensoMATCH – Surface Metrology Software for Accurate Bullet Comparison


In order to match a bullet to a firearm, a skilled examiner usually makes use of a microscope to compare the striations on all existing ‘land areas’ on the bullet with the land areas on a known bullet fired from the firearm. Even though this process has been reliable, it is subjective and tiresome.


Sensofar works to offer quantitative data on bullet lands using optical 3D metrology. SensoMATCH® is the latest program that offers complete automation of IC and bullet comparison. In general, this process comprises of five steps that are as follows:

  • Land surface measurements
  • IC extraction
  • IC comparison (CCFmax)
  • Bullet comparisons: new automated comparison score (SAM)
  • Top N list analysis

IC surface pairs are compared mathematically by extracting mean profiles from each surface and a cross correlation function (CCFmax) is calculated. The CCFmax value for identical profiles is 1.0. Lower correlations generate a very low CCFmax value, typically ranging from 0.2 to 0.4. Therefore higher scores signify the confidence level of a match.

The process of comparison scales up very quickly, which results in 10,800 scores in 300 matrices by comparing 15 unknown bullets to 20 known bullets.

SensoMATCH® Streamlines Bullet Comparison

To make the analysis process simple, one can calculate an individual composite score for each bullet pair which is referred to as Sequence Average Maximum (SAM). SAM offers a precise indication of a match between bullets. The user gives the threshold value which is used for identifying matches.

The complete John Hamby dataset of 15 vs. 20 bullets which accounts to a total of 10,800 comparisons can be processed in around 4 seconds. This comparison results in a spreadsheet which finds the top matches for each unknown bullet.

Key Features

The main features of the SensoMATCH® are as follows:

  • Missing lands compatibility
  • SensoMAP template for IC comparison makes use of comparison parameters and customized data processing
  • Training mode
  • This approach to data analysis can be made by using various optical metrology systems which includes the Sensofar series of optical metrology systems
  • Useful for calculating statistical values for ‘Known Matches vs. Known Non-Matches’ to define SAM thresholds

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