Abstract
Several methods are available for shooting range estimation based on pellets pattern on the target that have a remarkable degree of accuracy. The task is usually approached working under the assumption that the entire distribution of pellets is available for examination. These methods fail, however, when the victim has been hit by a portion of the pattern only. The problem can be solved with reasonable accuracy when there are areas of void in the victim that are adjacent to the area struck by pellets. This study presents a method that can be used in precisely this type of situation, allowing the estimation of shot distance in cases of partial pellet patterns. It is based on collecting distributions in test shots at several distances, and taking samples in the targets, constrained by the shape of the void and the pellet hit areas. Statistical descriptors of patterns are extracted from such samples, and fed into a neural network classifier, estimating shot ranges of distance.
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