The scale of contraband in security X-ray image is changeable and its posture is different, which brings great difficulties to automatic identification. To address this problem, an X-ray target detection algorithm based on pyramid convolution and strip pooling is proposed. First, pyramid convolution is introduced based on CenterNet, a one-stage anchor free frame target detection framework. Then, a pyramid hourglass network is proposed to enrich the receptive field of the hourglass-104 feature extraction network and enhance the ability of multi-scale feature extraction. Second, the introduction of strip pooling can capture the global information of the image context. It can also prevent information interference of irrelevant areas and consider local detail information. Finally, to enhance the performance of the scale prediction branch in the training process, the training loss of the prediction target scale branch is replaced by the intersection over union (loU) loss function. The ablation experiment results show that the average accuracy (mAP50) of the enhanced network is improved from 86.6% to 88.3%, and the accuracy is significantly improved.