Image Processing Automation with Feedback-Driven Prompting
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Solution Overview
Problem
Current image recognition technologies in image processing are inaccurate, leading to ineffective prompting for users based on recognition results, resulting in poor universality.
Innovation Solution
A method and apparatus for image processing that includes initiating a camera to capture an image, analyzing it to determine a recognition result, and retrieving prompt content based on the result to inform the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If image recognition technology is used, then image processing can be automated, but recognition accuracy is insufficient
Solution Approach 1:
The patent implements a feedback mechanism where the system not only performs image recognition but also provides prompts based on recognition results, allowing users to verify and correct recognitions. This feedback loop continuously improves recognition accuracy by learning from user corrections and adjusting the recognition model accordingly.
Solution Approach 2:
The system performs preliminary actions by pre-processing images, extracting key features, and preparing recognition data before actual recognition occurs. This preliminary preparation enables more accurate recognition by ensuring the image is optimally prepared and contextual information is readily available.
2Ease of operation
If recognition results are used to generate prompts, then user guidance can be provided, but prompt effectiveness is insufficient
Solution Approach 1:
The patent applies local quality by providing customized prompts based on specific recognition results and contextual information. Instead of generic prompts, the system generates localized guidance tailored to the specific image content, object type, and user needs, thereby improving both prompt effectiveness and accuracy.
Solution Approach 2:
The system changes parameters such as prompt tone, detail level, and guidance focus based on the recognition result and user profile. By dynamically adjusting these parameters, the system optimizes prompt effectiveness for different scenarios while maintaining high reliability through context-aware parameter selection.
3Extent of automation
If image analysis is performed to determine recognition results, then processing can be automated, but universality is poor
Solution Approach 1:
The patent implements universality by designing a multi-functional system that can handle various image types, objects, and scenarios through a single unified platform. The system uses adaptable recognition models and configurable prompt generation that work across diverse applications, making the automated image analysis universally applicable rather than limited to specific domains.
Data Source
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AI summary
The present disclosure relates to a method, apparatus, electronic device and storage medium for image processing. The method comprises: in response to detecting a triggering operation on a display interface, initiating a camera apparatus to capture, based on the camera device, an image to be processed including a target object (S110); determining a target recognition result corresponding to the target object by analyzing the image to be processed (S120); and retrieving a target prompt content corresponding to the target recognition result to prompt a target user based on the target prompt content (S130).