Mixed Media Reality Client Server Architecture for Image Recognition
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Solution Overview
Problem
There is a gap between printed media and electronic media, with no mechanism for publishers to easily migrate printed content into electronic form with augmented content, and existing image recognition technologies struggle with low-quality images from mobile devices, requiring improved speed and accuracy in image recognition and handling multiple recognition algorithms.
Innovation Solution
A Mixed Media Reality (MMR) system that includes mobile devices, an MMR gateway, and an MMR matching unit, which uses a client-server architecture with various modules for image recognition, preprocessing, and data retrieval, enabling peer-to-peer communication and dynamic load balancing to improve image recognition speed and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If image recognition is performed on low-quality images from mobile devices, then accessibility to printed media is improved, but recognition accuracy deteriorates
Solution Approach 1:
The system segments the image recognition task into multiple processing stages: initial feature extraction, candidate matching, and verification. By dividing the recognition process into discrete steps, the system can handle low-quality images more effectively at each stage rather than attempting single-pass recognition.
Solution Approach 2:
The system performs multiple recognition attempts with different algorithms and parameters on the same low-quality image. Rather than relying on a single recognition pass, it applies excessive processing actions (multiple algorithms, adjusted thresholds) to compensate for the poor image quality and increase the probability of successful recognition.
2Reliability
If multiple recognition algorithms are deployed to improve accuracy, then recognition reliability is improved, but device complexity increases
Solution Approach 1:
The system dynamically selects and configures recognition algorithms based on image quality assessment. Rather than running all algorithms simultaneously on every image, it adapts the recognition pipeline to the specific characteristics of each input image, reducing unnecessary computational complexity while maintaining reliability.
Solution Approach 2:
The system introduces an intermediary image quality assessment module that evaluates low-quality images before processing. This intermediary component determines which recognition algorithms to apply and in what order, mediating between the raw low-quality input and the multiple recognition algorithms to optimize system complexity.
3Speed
If image processing speed is increased to improve user experience, then response time is improved, but processing accuracy deteriorates
Solution Approach 1:
The system performs preliminary feature extraction and candidate identification before executing the full recognition pipeline. By pre-processing images to extract key features and identify potential matches early in the workflow, the system reduces the computational burden of subsequent steps while maintaining accuracy.
Solution Approach 2:
The system implements a multi-stage filtering approach where obvious mismatches are quickly eliminated in early stages, allowing the system to skip detailed analysis for clearly incorrect candidates. This rushing through of obvious failures enables faster processing while preserving accuracy for ambiguous cases that require thorough analysis.
Data Source
AI summary
The mobile device includes a client that has a number of modules, and the MMR Gateway and MMR matching unit are implemented as a server that has a number of modules. The implementation of the MMR system as a client and a server is advantageous because the modules may be distributed among the client and the server in a variety of configurations. The present invention includes a capture module, a preprocessing module, a feature extraction module, a retrieval module, a send message module, an action module, a prediction module, a feedback module, a sending module, an MMR database, a streaming module, an e-mail module, a voice recognition system and an audio database. These modules and systems are operational upon the client or the server.