  Prohibited items detection in X-ray images often plays an important role in
protecting public safety, which often deals with color-monotonous and
luster-insufficient objects, resulting in unsatisfactory performance. Till now,
there have been rare studies touching this topic due to the lack of specialized
high-quality datasets. In this work, we first present a High-quality X-ray
(HiXray) security inspection image dataset, which contains 102,928 common
prohibited items of 8 categories. It is the largest dataset of high quality for
prohibited items detection, gathered from the real-world airport security
inspection and annotated by professional security inspectors. Besides, for
accurate prohibited item detection, we further propose the Lateral Inhibition
Module (LIM) inspired by the fact that humans recognize these items by ignoring
irrelevant information and focusing on identifiable characteristics, especially
when objects are overlapped with each other. Specifically, LIM, the elaborately
designed flexible additional module, suppresses the noisy information flowing
maximumly by the Bidirectional Propagation (BP) module and activates the most
identifiable charismatic, boundary, from four directions by Boundary Activation
(BA) module. We evaluate our method extensively on HiXray and OPIXray and the
results demonstrate that it outperforms SOTA detection methods.
