Image Frame Routing to Element Detectors
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Solution Overview
Problem
Current image recognition technologies face challenges in efficiently detecting and processing embedded machine-readable links within images, such as barcodes and watermarks, to access associated digital resources, particularly in dynamic and varied visual content environments.
Innovation Solution
A system comprising a processor and machine-readable storage medium that routes image frames to multiple element detectors for recognition, using a combination of round robin and adaptive routing strategies to optimize processing, and retrieves resources associated with recognized elements, such as QR codes or facial recognition, to access external content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple element detectors are used to detect different types of embedded elements, then the detection capability and accuracy are improved, but the system complexity and processing time increase
Solution Approach 1:
The system divides the image processing task into multiple specialized element detectors, each responsible for detecting specific types of embedded elements (barcodes, QR codes, watermarks, etc.). This segmentation allows each detector to be optimized for its specific detection task, improving overall detection accuracy while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The router component serves as a universal coordinator that manages multiple specialized element detectors. It receives image frames, determines which detectors should process each frame, and coordinates their operation. This multi-functional router enables the system to handle diverse element types without requiring separate independent systems for each detector type.
2Productivity
If multiple element detectors process image frames simultaneously, then the detection speed is improved, but the resource consumption and processing overhead increase
Solution Approach 1:
The system implements dynamic routing where the router adaptively determines which element detectors should process each image frame based on the specific content and characteristics of that frame. This dynamic allocation ensures that only necessary detectors are activated for each frame, improving processing speed by parallelizing necessary detections while reducing resource consumption by avoiding unnecessary detector activation.
Solution Approach 2:
The router uses feedback from image analysis to dynamically adjust which element detectors receive which image frames. By analyzing frame characteristics and routing decisions, the system learns to optimize the distribution of image frames to detectors, balancing processing speed and resource consumption based on actual detection needs rather than using a fixed allocation strategy.
3Adaptability or versatility
If image frames are routed to multiple detectors, then the detection coverage is improved, but the processing time and computational load increase
Solution Approach 1:
The router performs preliminary analysis of each image frame to determine which element detectors should process it before actual detection begins. This preliminary routing action allows the system to prepare detection tasks in advance, ensuring comprehensive detection coverage by selecting appropriate detectors while minimizing processing time by avoiding unnecessary detector activation and reducing computational overhead.
Data Source
AI summary
Examples disclosed herein relate to image recognition instructions to receive a plurality of image frames, route each of the plurality of image frames to at least one of a plurality of element detectors, determine whether the respective one of the plurality of element detectors has recognized an embedded element and, in response to determining that the respective one of the plurality of element detectors has recognized the embedded element, cause a resource associated with the recognized embedded element to be retrieved.