Framework for Feature Matching in Synthetic Multi-View X-ray Imaging Using SIFT (Journal of Academic Research, 2024)
This paper presents a framework for evaluating the performance of the Scale Invariant Feature Transform (SIFT) algorithm in matching features within synthetic multi-view X-ray images. The research supports the development of the kinetic depth X-ray imaging (KDEX) technique, which enhances luggage scan interpretation at airport security checkpoints.Two experiments were conducted with identical input imagery. The first experiment applied SIFT directly to color-coded X-ray views, while the second experiment involved segmenting the imagery into material classes before applying SIFT to each class. The matching results from both experiments will be analyzed to assess the algorithm's effectiveness as the angular separation between X-ray views increased.This study lays the groundwork for further research into automated feature matching in security screening applications, offering a promising approach to improving X-ray image interpretation.