DETECTION OF FORBIDDEN OBJECTS IN X-RAY IMAGES
Date
2017-04-02
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Abstract
Detection of forbidden objects in x-ray scan images has become an important issue
for customs border and airport security. Most border screening depends on the
manual detection of possible forbidden objects by human experts.
In this thesis, we present a system for detection of possible forbidden objects in x-ray
scan images with minimal amounts of missing object (false negatives) and false
alarms (false positives). Firstly, pre-processing steps are applied to obtain a clearer
image. Then, segmentation is used to locate the potential objects in images. Feature
extraction with two algorithms, local binary pattern and histogram oriented gradients,
and classification with support vector machine are next steps in the system.
The system is tested using handguns as the forbidden objects in question. The
experimental results show that the system can effectively detect the handguns in x-ray scan images with minimal amounts of missing objects automatically.
Description
X-RAY GÖRÜNTÜLERİNDE YASAK NESNELERİN TESPİT EDİLMESİ