Gun Detection with Faster R-CNN in X-Ray Images

In this article, Faster R-CNN object detection algorithm is used for automatic weapon detection in X-Ray bag images obtained from security points. In the proposed method, Faster R-CNN model was fed by creating 2 different 3 band images. In the first one, the 3 bands of the image are equalized to the high energy values obtained from the X-Ray device. In the other one, 1st band is equalized to high values, 2nd band is equalized to low values and the 3rd band is equalized to the difference between high energy and low energy values. Performance values of the two different image generation techniques that fed the deep learning model were compared. In the study, X-Ray dataset provided by HTR Company was used. When the results are evaluated, it is seen that Faster R-CNN method can be used in weapon detection with very high performance as a deep learning model and the method of creating images that feed the model has an effect on object detection performance.