Cargo Inspection System Using X-Ray Image Analysis
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Solution Overview
Problem
Current radiation security inspection methods, such as dual-energy material recognition and X-ray imaging, fail to provide comprehensive insights into cargo compliance, secret cargo detection, and abnormal transportation behavior, relying heavily on human expertise and scrutiny as throughput increases.
Innovation Solution
A method and system that process transmission images of cargoes to extract features, determine cargo information, and provide treatment suggestions by analyzing the images and manifest data, using techniques like histogram description features, dictionary establishment, and probability calculations to assess consistency and risk levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional dual-energy material recognition and X-ray imaging methods are used, then basic cargo composition and shape information can be obtained, but comprehensive insights into cargo compliance, secret cargo detection, and abnormal transportation behavior cannot be provided
Solution Approach 1:
The inspection system segments the analysis process into multiple specialized modules: cargo composition analysis, stack mode recognition, transportation behavior analysis, and compliance verification. Each module processes specific aspects of cargo information independently, then integrates results to provide comprehensive insights without requiring a completely complex new system architecture.
Solution Approach 2:
The X-ray imaging system is enhanced with multi-functional analysis capabilities that can simultaneously perform basic material recognition, cargo stacking pattern identification, transportation behavior verification, and compliance checking. This allows a single inspection system to provide comprehensive insights across multiple dimensions of cargo security and compliance.
2Measurement precision
If security staff rely on rich experience and closer scrutiny of image content, then problems such as cargo compliance and abnormal behavior can be answered, but inspection efficiency decreases as throughput increases
Solution Approach 1:
The system replaces manual scrutiny and human expertise-based analysis with automated image processing algorithms and machine learning models. These computational systems analyze cargo images, detect stacking patterns, verify transportation compliance, and identify abnormalities automatically, maintaining high accuracy while enabling rapid processing of increased throughput volumes.
Solution Approach 2:
The inspection system performs self-analysis by automatically extracting cargo information, comparing it against known compliance rules and transportation patterns, and generating security assessments without requiring continuous human intervention. This automated self-service capability maintains precision while scaling to handle high throughput efficiently.
3Device complexity
If only basic material recognition and shape analysis are performed, then the inspection process remains simple, but important security questions such as secret cargo detection and abnormal behavior identification cannot be answered
Solution Approach 1:
The system extends basic two-dimensional X-ray image analysis into additional analytical dimensions by examining cargo stacking patterns, transportation route compliance, temporal behavior patterns, and contextual security data. This multi-dimensional analysis approach answers security questions that cannot be detected through traditional material and shape recognition alone, enhancing reliability without excessive complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances efficiency and accuracy in cargo inspection by automatically analyzing cargo types, detecting abnormal behaviors, and providing proposed treatment suggestions, addressing the limitations of existing methods by providing intelligent and automated deductions.
Implementation Method 1
acquiring a transmission image of the inspected cargoes
Implementation Method 2
transmission image of the inspected cargoes
Data Source
Figure 1A~2
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AI summary
The present disclosure discloses a method and system for inspecting cargoes. The method comprises: acquiring a transmission image of the inspected cargoes; processing the transmission image to acquire an interested region; extracting features from the interested region, and determining cargo information of the inspected cargoes according to the extracted features; and providing a proposed treatment suggestion of the cargoes based on the determined cargo information and at least a part of information in a manifest.