X-ray Container Inspection Using Texture Feature Distinctness
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Solution Overview
Problem
Current security inspection technologies lack effective means for automatic detection of secretly carried articles in containers, relying heavily on manual judgment and requiring significant manpower, which is inefficient and prone to errors.
Innovation Solution
An inspection device and method utilizing Digital Radiography (DR) images and X-ray scanning technology to automatically detect cargo regions with unique texture features, assisting manual judgment by identifying suspicious articles and enhancing inspection accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual judgment is used to inspect container images, then detection accuracy can be maintained through human expertise, but inspection efficiency is low and significant manpower is required
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated computer-based image analysis system. The computing device automatically processes radiation images, extracts features, and identifies suspicious articles, substituting human operators with automated computational methods to improve inspection efficiency and productivity.
Solution Approach 2:
The inspection system performs self-service by automatically analyzing images without requiring continuous human intervention. The computing device independently executes the inspection workflow including image processing, feature extraction, and article identification, enabling the system to serve itself in the detection process while maintaining high productivity.
2Productivity
If automated detection is implemented, then inspection efficiency is improved, but detection accuracy may deteriorate due to lack of human judgment expertise
Solution Approach 1:
The patent segments the detection task into distinct computational stages: image preprocessing, feature extraction, and suspicious article identification. Each stage processes specific aspects of the image data independently, allowing the system to maintain high detection accuracy through specialized processing while achieving automated efficiency.
Solution Approach 2:
The system performs partial automated detection by focusing on identifying suspicious articles with unique texture features rather than attempting to classify all cargo types. This selective approach maintains high detection accuracy for critical items while achieving automation efficiency, without requiring the system to perfectly identify every article type.
3Reliability
If comprehensive manual inspection is performed on all container images, then detection thoroughness is improved, but time consumption and manpower requirements increase significantly
Solution Approach 1:
The patent extracts and focuses specifically on regions with unique texture features that indicate suspicious articles, rather than requiring comprehensive manual inspection of entire container images. This extraction approach maintains detection thoroughness by targeting critical areas while significantly reducing the time required compared to examining all image regions manually.
Solution Approach 2:
The system performs preliminary automated processing of radiation images before detailed analysis, including preprocessing and feature extraction. This preliminary action prepares the data in advance, enabling faster and more thorough detection of suspicious articles by pre-identifying regions of interest that require further examination.
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
Improves the accuracy and efficiency of detecting secretly carried articles, reducing the reliance on manual image judgment and enhancing the effectiveness of security inspections in containers.
Implementation Method 1
Radiation imaging achieves the purpose of non-invasive inspection by performing transmission imaging on cargos
Data Source
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AI summary
A method for inspecting a container and an inspection device are disclosed. X-ray scanning is performed on the inspected container to obtain a scanned image. The scanned image is processed to obtain a region of interest. Features of texture units included in the region of interest are calculated. Local descriptions of the texture units are formed based on the features of the texture units. Distinction of each local point is calculated from a local description of each of the texture units so as to obtain a local distinct map of the region of interest. It is determined whether there is an article which is secretly carried in the inspected container using the local distinct map.