Homogeneity Analysis for Cargo Inspection Image Classification
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Solution Overview
Problem
It is challenging to detect inhomogeneities in images, particularly inspection images, especially when dealing with a large number of images or those with varying contrast, which can pose security threats by hiding objects like weapons or dangerous materials.
Innovation Solution
A method and system that determine the degree of homogeneity in images by analyzing patterns and variations, enabling classification into categories based on a homogeneity threshold, and facilitating the detection of inhomogeneities across different contrast levels, thereby assisting in identifying hidden objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection of images is performed, then detection accuracy may be maintained, but inspection efficiency deteriorates when dealing with large numbers of images
Solution Approach 1:
An automated analysis system acts as an intermediary between the large volume of images and the human inspector. The system calculates homogeneity metrics and generates visualizations that highlight suspicious regions, enabling inspectors to quickly identify which images require detailed manual examination without having to manually inspect every single image.
Solution Approach 2:
The system performs preliminary automated analysis of all images before human inspection. By pre-calculating homogeneity metrics and identifying suspicious regions in advance, the system prepares the data in a way that allows human inspectors to focus their attention only on images that require detailed examination, thereby improving overall inspection efficiency.
2Measurement precision
If images with varying contrast are inspected manually, then all detail levels can be examined, but detection difficulty increases due to the large number of images required
Solution Approach 1:
The system automatically adjusts contrast parameters to optimize the visibility of inhomogeneities. By dynamically modifying contrast levels based on image characteristics, the system enhances the detectability of hidden objects without requiring manual inspection of multiple contrast versions of each image.
Solution Approach 2:
The system adds a new dimension of analysis by calculating homogeneity metrics that quantify the uniformity of image regions. This numerical metric provides an additional layer of information that helps inspectors prioritize images containing potential threats, reducing the overall inspection complexity.
3Reliability
If all images are inspected in detail, then security coverage is maximized, but time consumption increases significantly
Solution Approach 1:
The system performs a simplified initial assessment of all images using automated homogeneity analysis, then applies detailed inspection only to images that exceed certain threshold values. This partial application of full inspection resources maintains security coverage while dramatically reducing total inspection time.
Solution Approach 2:
Automated homogeneity analysis serves as an intermediary filtering layer that identifies suspicious images for detailed review. This intermediate step maintains comprehensive security coverage by ensuring all images are at least preliminarily assessed, while reducing time consumption by eliminating the need for detailed manual inspection of obviously homogeneous images.
Data Source
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AI summary
In one embodiment, the disclosure relates to a method for determining a degree of homogeneity in one or more inspection images of cargo in one or more containers, comprising: determining whether a zone of interest in one or more processed inspection images comprises one or more patterns, wherein the one or more processed inspection images are processed from one or more inspection images generated by an inspection system configured to inspect the one or more containers; and in the event that one or more patterns is determined and that a variation in the determined one or more patterns is identified, classifying the one or more inspection images as having a degree of homogeneity below a predetermined homogeneity threshold.