Baggage Sorting Video Coding with Image Ranking
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Solution Overview
Problem
Existing methods for sorting baggage at airports face challenges when barcodes are difficult to read or databases are inaccessible, leading to inefficiencies in automated sorting systems.
Innovation Solution
A method that involves acquiring digital images of baggage from multiple viewpoints, using video coding to detect characteristic elements, compute scores, and rank images for prioritized display to human operatives, allowing for manual data input and utilizing local flights databases for robust information retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated sorting systems are used with barcode reading and OCR analysis, then sorting speed is improved, but reliability deteriorates when barcodes are damaged or databases are inaccessible
Solution Approach 1:
The system captures multiple images of the baggage label from different angles and positions before the sorting decision is required. This preliminary action ensures that even if some images are poor quality, readable images are already available to fallback on when automated barcode/OCR methods fail, thus maintaining reliability without sacrificing sorting speed.
Solution Approach 2:
The system changes the parameter of image acquisition by capturing images at multiple different positions and angles rather than a single viewpoint. This increases the probability of obtaining readable images of damaged or obscured labels, thereby improving system reliability while maintaining automated processing speed.
2Reliability
If multiple images are displayed to operatives for manual data input, then reliability is improved, but time consumption increases
Solution Approach 1:
The system pre-ranks multiple baggage images based on their likelihood of containing readable label information before presenting them to the operative. This preliminary ranking ensures that the most useful images are displayed first, allowing operatives to quickly find readable labels without manually reviewing all images, thus improving data input accuracy while minimizing time loss.
Solution Approach 2:
The system replaces the mechanical/manual process of operatives randomly selecting images with an automated intelligent ranking system that uses image analysis algorithms. This substitution automatically identifies and prioritizes images with the highest probability of containing readable text, reducing the time operatives need to spend searching for useful images while improving data accuracy.
Data Source
AI summary
A method of sorting baggage at an airport, which method comprises acquiring a plurality of digital images (IN) of a piece of baggage, which piece of baggage carries an unambiguous identification label bearing textual information about a flight, the method further comprising video coding in which a computer unit automatically detects the presence of characteristic elements of the unambiguous identification label in the digital images, computes a score for each of the digital images on the basis of a count of the characteristic elements, ranks the images as a function of their respective scores, and displays the images on a screen (132) as a function of the ranking.