Two-Stage Image Identity Recognition for Similar Object Verification
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Solution Overview
Problem
Existing image data processing systems struggle to accurately identify user identities in highly similar groups, leading to recognition failures and service execution issues.
Innovation Solution
Perform first-type identity recognition on a target object using a similar object database, followed by second-type identity recognition through K pattern recognition services to confirm the object's identity, and output a similar ID for service execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single-type identity recognition is used for processing image data, then processing speed is fast, but object recognition accuracy is low for highly similar objects
Solution Approach 1:
The recognition system is segmented into two distinct modules: first-type identity recognition for initial filtering and second-type identity recognition for final confirmation. This segmentation allows each module to specialize in specific recognition tasks, improving overall accuracy for highly similar objects while maintaining system manageability through modular architecture.
Solution Approach 2:
The system applies partial action by using the first-type recognition for most cases (initial filtering) and only activating the second-type recognition when high similarity is detected. This excessive action (applying additional recognition type) is strategically used only when needed, balancing accuracy improvement with computational efficiency.
2Measurement precision
If multiple pattern recognition services are deployed to improve accuracy, then object recognition accuracy improves, but processing time increases
Solution Approach 1:
The system implements periodic action through a two-stage recognition process where the first-type recognition runs continuously for all inputs, and the second-type recognition is periodically activated only when the first stage identifies high-similarity cases. This periodic deployment of additional recognition services minimizes overall processing time while maintaining high accuracy for difficult cases.
Solution Approach 2:
Multiple pattern recognition services (second-type) are deployed as excessive action only when necessary for highly similar objects, rather than applying them to all recognition tasks. This partial deployment strategy ensures high accuracy for challenging cases while avoiding unnecessary computational overhead for straightforward recognitions.
3Reliability
If comprehensive identity verification is performed, then service execution reliability is ensured, but system complexity increases
Solution Approach 1:
The verification system is segmented into hierarchical levels: first-type identity recognition provides basic verification, and second-type identity recognition provides enhanced verification for suspicious cases. This segmentation ensures comprehensive verification reliability through multiple checkpoints while keeping the system complexity manageable through clear modular boundaries and standardized interfaces.
Data Source
AI summary
An image data processing method includes a first-type identity recognition performed on a target object in an image data stream. In response to the first recognition result indicating that the target object is a similar object in the similar object database, a similar identity document (ID) associated with the similar object is acquired. In addition, K pattern recognition services configured for the similar ID are also acquired. A second-type identity recognition is performed on the target object in the image data stream through the K pattern recognition services respectively to obtain K second recognition results. In response to the K second recognition results indicating that the target object is the similar object, the similar ID to the application client to cause the application client to execute an application service based on the similar ID.