Image Identity Recognition Using Multi-Pattern Look-Alike Verification
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Solution Overview
Problem
Existing image data processing systems struggle to accurately identify the real identity of users within highly look-alike groups, leading to identification failures and reduced accuracy in executing services like payments.
Innovation Solution
Implement a method and apparatus that perform first-type identification on a target object using a look-alike object database, followed by K pattern identification services to confirm the identity, ensuring accurate recognition by outputting a look-alike ID when multiple authentications match.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single pattern identification is used for look-alike objects, then identification speed is maintained, but identification accuracy deteriorates
Solution Approach 1:
The identification system is segmented into multiple independent pattern identification services (first pattern, second pattern, third pattern, etc.). Each service performs identification using a different pattern or algorithm, and their results are aggregated to make the final determination. This segmentation allows the system to maintain high accuracy through multiple verification points while keeping each individual service relatively simple.
Solution Approach 2:
The system changes the identification parameters by using multiple different patterns (e.g., different feature extraction methods, different comparison algorithms, or different weightings) to identify the same look-alike object. By varying the identification parameters across multiple services, the system can compensate for the weaknesses of any single pattern and achieve more accurate results.
2Reliability
If multiple pattern identification services are deployed, then identification reliability is improved, but processing time increases
Solution Approach 1:
The system performs preliminary action by pre-configuring multiple pattern identification services and their corresponding patterns before actual identification is needed. The services are prepared in advance with their algorithms and parameters, so when identification is required, they can execute quickly without needing to set up or configure anything during the actual processing. This reduces the time penalty of having multiple services.
Solution Approach 2:
The multiple pattern identification services operate independently and autonomously, each performing its identification task without requiring manual intervention or coordination. The system automatically collects and aggregates their results, allowing parallel execution that minimizes total processing time while maintaining high reliability through multiple independent verification paths.
Data Source
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AI summary
Disclosed in embodiments of the present application are an image data processing method and apparatus, a computer device, a computer-readable storage medium, and a computer program product. The method comprises: when performing first-type identity recognition on a target object in an image data stream, if a first recognition result indicates that the target object is a similar object in a similar object database, obtaining similar identity information associated with the similar object, and obtaining, from a similar service configuration database associated with the similar object database, K pattern recognition services configured for the similar identity information; performing second-type identity recognition on the target object in the image data stream by means of the K pattern recognition services to obtain K second recognition results; and if the K second recognition results all indicate that the target object is a similar object, outputting the similar identity information to an application client, such that the application client executes application services on the basis of the similar identity information.