Security inspection system and method based on depth neural network

Abstract

The invention discloses a security inspection system and method based on a depth neural network. The security inspection system comprises an X-ray imaging module, a detection model training learning module, an object identification module and a security management module, wherein the output end of the X-ray imaging module is connected with the input end of the object identification module, the object identification module is bidirectionally connected with the detection model training learning module, and the output end of the object identification module is connected with the input end of thesecurity management module. Based on the color feature segmentation of X-ray images and synthesis of detection images of multiple planes, a detection model of the depth neural network is established,and big data are used to train and learn the features of common articles to identify and classify rotating, telescopic and deforming objects through a detector.

Description

technical field [0001] The invention belongs to the technical field of security inspection, and in particular relates to a security inspection system and method based on a deep neural network. Background technique [0002] With the rapid development of the economy, high-speed rail, airplanes, etc. have become an indispensable means of transportation for people's daily travel. However, passengers who intentionally or unintentionally carry dangerous goods on vehicles have become the biggest threat to transportation safety. X-ray security inspection machines play an important role in the safety detection of dangerous goods and in ensuring the safety of transportation vehicles. However, the traditional X-ray security inspection machine requires staff to carefully check the X-ray luggage image to determine whether it contains dangerous goods. The device is low in intelligence, and the cost of manual inspection is high. At the same time, there may be misjudgments and omissions. ,...

AI Technical Summary

Problems solved by technology

[0008] Aiming at the problems existing in the existing X-ray baggage detection technology, such as low accuracy of object detection and positioning, unclear categories of dangerous goods, and low degree of intelligence in the detection process, an X-ray intelligence based on color segmentation and multi-plane deep neural network is proposed. Security inspection device and method to solve the problem of detection and identification of items carried in daily luggage packages

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