Automated Body Scanner Target Recognition via Humanoid Coordinate Mapping
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Solution Overview
Problem
Current automated target recognition (ATR) systems in body scanners have poor performance in detecting concealed security threats with high false alarm rates, limiting their effectiveness and requiring significant human intervention, which is inefficient and prone to errors.
Innovation Solution
The implementation of a database comparison system using humanoid coordinates to align and compare scanned images, allowing features to be classified based on their commonality within a population, thereby identifying uncommon features as potential threats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated target recognition systems are used in body scanners, then throughput and privacy are improved, but detection accuracy deteriorates with high false alarm rates
Solution Approach 1:
The system creates a digital copy of the scanned image and compares it against a database of reference images stored in memory. This copying approach enables automated comparison without requiring human analysts, thereby maintaining high throughput while improving detection accuracy through systematic pattern matching.
Solution Approach 2:
The system provides feedback by displaying the scanned image on a monitor and highlighting potential threats or anomalies detected during the database comparison process. This feedback mechanism allows the system to iteratively improve its detection accuracy while maintaining automated operation and high throughput.
2Reliability
If human analysts review body scanner images, then detection accuracy is improved, but productivity deteriorates due to manual processing requirements
Solution Approach 1:
The system performs self-service by automatically comparing scanned images against a database of reference images and identifying potential threats without requiring human intervention. This automation maintains high detection accuracy through systematic pattern recognition while dramatically improving productivity by eliminating manual processing time.
Solution Approach 2:
The patent replaces the mechanical human analysis process with an automated computer-based system that uses image processing algorithms and database comparison to detect threats. This substitution eliminates the productivity constraints of manual review while maintaining or improving detection accuracy through consistent, objective analysis.
3Reliability
If body scanners are used to detect concealed objects, then security screening capability is improved, but device complexity increases due to multiple radiant energy systems
Solution Approach 1:
The system achieves universality by using a single body scanner capable of detecting multiple types of concealed objects through different radiant energies (x-rays, microwaves, millimeter waves, infrared, terahertz, ultrasound). This multi-functional approach improves security screening capability while managing device complexity through integrated processing and a unified database comparison system.
Solution Approach 2:
The system manages complexity by changing the detection parameters dynamically - selecting appropriate radiant energy types and scanning modes based on the specific security screening requirements. This parameter flexibility allows the system to maintain high security screening capability across different scenarios while simplifying operation through automated parameter selection and database comparison.
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
This approach enhances the detection of security threats by reducing false alarms and eliminating the need for human image analysis, improving the overall efficiency and accuracy of body scanner systems.
Implementation Method 1
These devices operate by detecting radiant energy that has been modulated by or emitted from the body of the person being examined. Radiant energies used include: x-rays, microwaves, millimeter waves, infrared light, terahertz waves, and ultrasound.
Implementation Method 2
some body scanners operate passively, collecting radiant energy that has been thermally emitted from the person's body and surrounding area. Examples of this are infrared and millimeter wave sensitive cameras.
Data Source
AI summary
Body scanners are used in airports and other secured facilities to detect weapons, explosives, and other security threats hidden under persons' clothing. These devices use x-rays, millimeter waves and other radiant energy to produce an electronic image of the person's body and any concealed objects. Examination of these images by human analysts is slow, expensive, and subject to privacy concerns. The Invention provides automated analysis by comparing each image against a database of previous scans, using a plurality of subjects with different body types. This comparison is facilitated by digitally mapping each body scanner image to humanoid coordinates. This overcomes the failings of the prior art by allowing each anatomic location on one person to be referenced to the same anatomic location on all other persons.