Analysis of object recognition characteristics in X-ray security imaging
X-ray scanning is a crucial imaging technique for contraband inspection of packages duringsecurity checks. However,traditional manual recognition methods suffer from low efficiency and sus-ceptibility to subjective factors. To promote the development of automatic contraband identification technology,a progressive analysis of X-ray image recognition characteristics is conducted from three levels:data,task,and method. At the data level,the data and datasets of X-ray and visible light are compared separately,revealing the uniqueness of X-ray security images. At the task level,the com-plexity of the object recognition task of X-ray security images is deeply analyzed from multiple as-pects,such as data characteristics,industry supervision,and actual business requirements. At the method level,based on data and task characteristics,the specific methods and strategies for existing X-ray security image object recognition are classified and briefly described. The results indicate that X-ray image object recognition technology needs to cope with the dilemma caused by data characteris-tics,adapt to changes in industry supervision,deal with differences in the characteristics of inspected objects,and meet fine-grained regulatory requirements. In response to the challenges brought by cer-tain characteristics,effective strategies such as data preprocessing,data enrichment,occlusion pro-cessing,and multi-view fusion have emerged,presenting potential areas for improvement and expan-sion. This study's findings can offer targeted references and inspiration to researchers in the field,aid-ing them in better meeting the evolving requirements of security screening tasks.
万方数据
维普
