Acquisition UI Image Validation for Suspicious Object Detection
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Solution Overview
Problem
Existing systems at security checkpoints struggle to effectively detect prohibited objects due to malicious attempts to evade detection through image manipulation by operators, leading to inefficiencies and potential false alarms.
Innovation Solution
A system and method utilizing processing circuitries to analyze data from a user interface, determine image validity criteria, and apply a detection algorithm to identify suspicious elements, while filtering out irrelevant images using machine learning models to ensure consistent and effective detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If operators manually process images to detect prohibited objects, then detection capability is improved, but image manipulation by operators can evade detection and reduce reliability
Solution Approach 1:
The system implements feedback by analyzing user interface data to determine what processing operations were applied to generate the image, then using this feedback information to validate image authenticity and detect manipulation attempts before final detection
Solution Approach 2:
The system performs preliminary validation of image processing operations by checking user interface data before the image is fed to the detection algorithm, preventing manipulated images from reaching the detection stage
2Reliability
If the system processes all images through detection algorithms, then detection coverage is improved, but processing time and computational resources increase
Solution Approach 1:
The system extracts and analyzes user interface data separately from the main image detection process, identifying images that meet validity criteria before feeding them to the detection algorithm, thus filtering out irrelevant images early
Solution Approach 2:
The system applies partial processing by only feeding images that meet validity criteria to the detection algorithm, rather than processing all images, thereby reducing computational overhead while maintaining detection effectiveness
3Measurement precision
If the system validates image processing operations, then detection accuracy is improved, but system complexity increases
Solution Approach 1:
The system uses a multi-functional approach where the same processing circuitry that displays images on the user interface also captures and analyzes the user interface data to determine processing operations, eliminating the need for separate validation hardware
Solution Approach 2:
The user interface serves as an intermediary that both displays images to operators and provides data about processing operations to the validation system, simplifying the architecture by reusing existing components
Data Source
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AI summary
There are provided systems and methods comprising obtaining data displayed on a user interface, informative of one or more processing operations used to generate at least one given image informative of one or more elements acquired by an acquisition device, using the data to determine whether the at least one given image meets a validity criterion, and responsive to determining that the validity criterion is met, using the at least one given image, or data informative thereof, and a detection algorithm, to determine whether one or more suspicious elements are present in the at least one given image.