Luggage Detection Device CT Imaging Edge Accuracy
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Solution Overview
Problem
Conventional luggage scanning systems using CT imaging face challenges in accurately detecting luggage due to gaps in optical sensor coverage, spurious triggers from X-ray detectors, and discrepancies in edge detection, leading to false positives and negatives, which are difficult to interpret visually.
Innovation Solution
A luggage detection device and method that processes CT imaging data to generate slices, identifies regions for removal based on predefined rules, modifies slices by removing pixel data, and generates indicators for luggage detection, allowing for real-time visualization of false positives and negatives, and filters edges to eliminate spurious detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If optical sensors are used to detect luggage edges, then edge detection capability is improved, but gaps in sensing coverage and limited scan tunnel coverage cause false positives and negatives
Solution Approach 1:
The patent introduces an intermediary processing system that receives data from both optical sensors and X-ray detectors, reconciles their measurements, and produces a unified detection result. This mediator resolves the contradiction by integrating multiple detection sources to compensate for individual sensor limitations, thereby maintaining edge detection precision while improving overall reliability.
Solution Approach 2:
The patent merges the detection capabilities of optical sensors and X-ray detectors into a unified detection system. By combining the edge detection strength of optical sensors with the comprehensive coverage of X-ray detectors, the system achieves both high measurement precision and reliable detection without false positives or negatives.
2Reliability
If X-ray detectors are used to identify luggage edges, then coverage is improved, but spurious triggers from vibrations or external causes cause false detections
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors detection signals from X-ray detectors and compares them against expected patterns. When spurious triggers occur due to vibrations or external causes, the feedback loop identifies these anomalies and filters them out, maintaining reliable coverage while preserving measurement precision.
Solution Approach 2:
An intermediary processing layer is introduced between the X-ray detector and the final detection output. This intermediary validates X-ray detector signals, distinguishing genuine edge detections from spurious triggers caused by vibrations or external factors, thereby maintaining both coverage and precision.
3Reliability
If optical sensors and X-ray detectors are used together, then detection coverage is improved, but disagreement between spatial locations of bag edges increases complexity
Solution Approach 1:
The patent introduces an intermediary reconciliation system that receives data from both optical sensors and X-ray detectors at different spatial locations. This intermediary processes and harmonizes the disparate measurements, resolving disagreements about bag edge locations while maintaining the benefits of comprehensive coverage without overwhelming system complexity.
Solution Approach 2:
The patent segments the detection process into distinct processing stages: data acquisition from separate sensors, individual sensor processing, reconciliation of spatial discrepancies, and final unified detection. This segmentation manages the complexity of integrating multiple detection sources while maintaining reliable coverage.
4Productivity
If detection occurs in non-reconstruction domain of raw imaging data, then processing speed is improved, but difficulty in visual interpretation increases
Solution Approach 1:
The patent introduces an intermediary visualization layer that translates rapid processing results from the non-reconstruction domain into human-perceivable representations. This intermediary enables fast processing while maintaining visual interpretability, allowing users to understand detection results without sacrificing processing speed.
Data Source
AI summary
A luggage detection device is configured to detect luggage by generating computed tomography (CT) imaging slices. For each of the CT imaging slices, the luggage detection device is configured to identify at least one region within the CT imaging slice for removal based on at least one predefined rule, to remove pixel data associated with the at least one identified region within the CT imaging slice, to generate a pixel count representing a number of pixels in the modified CT imaging slice that include a value above a threshold pixel value, and to generate an object indicator based on a determination that the generated pixel count is above a threshold pixel count. The luggage detection device is further configured to display at least one of the plurality of CT image slices based on the presence of the corresponding baggage indicator.