Convolutional Neural Network for Headstamp Recognition
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2018-06-18
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en
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Abstract
Weapons and armor are transported all over the world after manufacture. One way
to connect the place of manufacturing to a cartridge is by using the headstamp, a
stamp on the bottom of the casing. This information could, for example, be used to
obtain information in conflicts or to get more insight into the exports of ammunition
of a country. In this bachelor thesis, I trained a convolutional neural network to
automatically detect and identify the characters of headstamp codes in order to
allocate armors all around the world to their country of origin. The trained CNN
had an accuracy of 71.33%. This result implies that a CNN can be used for the
recognition of characters of a headstamp code. Further research has to be done in
order to automatically recognize the characters in images of headstamp codes and
automatically use this information to obtain the manufacturer of the cartridge.
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Faculteit der Sociale Wetenschappen