Barcode Tracking via Correlation Filters and Periodic Decoding
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Solution Overview
Problem
Web-based applications for barcode scanning face computational challenges due to limited resources, leading to lag and inaccurate decoding, especially when dealing with multiple frames and fast movement, and not all devices have the necessary computing power or sensors to leverage additional data for improved tracking.
Innovation Solution
Implementing a method that decodes barcodes in initial and subsequent frames while tracking their positions in intermediate frames using a correlation filter, which predicts code locations based on image history and background structures, reducing computational load and improving accuracy without requiring additional sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous decoding is performed in every frame, then decoding accuracy is improved, but computational load and energy consumption increase significantly
Solution Approach 1:
The patent implements periodic decoding at key frames (initial frame and subsequent frames) while using correlation filters for tracking in intermediate frames. This periodic action reduces computational load and energy consumption while maintaining decoding accuracy by only performing full decoding when necessary, rather than continuously in every frame.
Solution Approach 2:
The patent applies preliminary action by performing decoding in advance at key frames to obtain code identities, then using correlation filters for tracking in intermediate frames. This preliminary decoding allows the system to predict code locations and maintain tracking without repeated full decoding operations, reducing energy consumption while preserving accuracy.
2Measurement precision
If decoding is performed in every frame, then tracking accuracy is improved, but processing speed and responsiveness deteriorate due to computational lag
Solution Approach 1:
The patent uses periodic decoding at key frames combined with continuous correlation filter tracking in intermediate frames. This approach maintains tracking accuracy by periodically updating code identities while improving processing speed by avoiding repeated full decoding operations, eliminating computational lag.
Solution Approach 2:
The patent introduces correlation filters as an intermediary mechanism between full decoding operations. The correlation filters maintain tracking accuracy in intermediate frames without requiring full decoding, acting as a mediator that preserves precision while enabling faster processing and improving overall system responsiveness.
3Measurement precision
If additional sensors are added to improve tracking, then tracking precision is improved, but device complexity increases
Solution Approach 1:
The patent applies self-service by using the existing camera and image processing capabilities to perform tracking through correlation filters. The system uses its own visual data and computational resources rather than requiring additional external sensors, maintaining tracking precision while avoiding increased device complexity.
Solution Approach 2:
The patent makes the existing camera and image processing system multi-functional by using it for both initial decoding and continuous tracking through correlation filters. This universal approach allows the same hardware to perform multiple functions (decoding and tracking) without requiring additional specialized sensors, reducing device complexity while maintaining precision.
4Measurement precision
If full decoding is performed continuously, then code identification accuracy is improved, but computational resources are depleted
Solution Approach 1:
The patent implements periodic full decoding at key frames (initial and subsequent frames) while using computationally efficient correlation filters for tracking in intermediate frames. This periodic approach maintains code identification accuracy by periodically updating code identities while conserving computational power by avoiding continuous full decoding operations.
Solution Approach 2:
The patent performs preliminary decoding at key frames to establish code identities, then uses correlation filters for tracking in intermediate frames. This preliminary action ensures accurate code identification while reducing computational power consumption by performing the intensive decoding operation only when necessary rather than continuously.
Data Source
AI summary
Image analysis is used to map objects in an arrangement. For example, images of a retail shelf are used to map items for sale on the retail shelf A first vector can used to identify a relative position of a first item on a shelf to a shelving diagram, and a second vector can be used to identify a relative position of a second on the shelf to the shelving diagram, using locations of optical codes (e.g., barcodes). Absolute positions can be calculated. In some configurations, multiple images having different fields of view are matched to an overview image.