Object Recognition Profiles for Cross-Device Image Enhancement
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Solution Overview
Problem
Existing image capture and sharing technologies do not effectively allow users to enhance or modify images to remove or add specific attributes, such as facial features or advertisements, in a personalized and automated manner across various devices and platforms.
Innovation Solution
A system and method that utilizes recognition software to identify individuals or objects in images, allowing for the creation of personalized enhancement profiles that can be stored on devices or servers, enabling automatic editing of attributes like facial features or advertisements based on user preferences, and transferring these profiles across different devices and platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If recognition software and editing software are integrated into the imaging device to enable automatic image enhancement, then user control and personalization of image attributes are improved, but device complexity increases
Solution Approach 1:
The system is divided into distinct software modules: recognition software for identifying objects/individuals, editing software for modifying attributes, and profile management software for storing preferences. This segmentation allows each module to perform its specific function independently, reducing overall system complexity while maintaining ease of operation.
Solution Approach 2:
An image profile acts as an intermediary between the user's enhancement preferences and the actual image processing. The profile stores configured attributes and editing parameters, mediating between user input and the automated editing process, thereby simplifying the user interface without requiring complex real-time processing logic.
2Adaptability or versatility
If image profiles are made transferrable across multiple devices and platforms, then adaptability and user convenience are improved, but data management complexity increases
Solution Approach 1:
Image profiles are designed as digital data structures that can be copied and transferred between devices. The profile contains all necessary configuration information in a standardized format, allowing exact replication across different imaging devices and platforms without requiring complex synchronization or conversion logic.
Solution Approach 2:
The image profile format is designed to be universal, compatible with multiple device types and platforms. This multi-functionality allows the same profile data structure to serve different devices (smartphones, tablets, computers, servers) without requiring device-specific adaptations, thereby improving adaptability while keeping data management straightforward.
3Productivity
If automated editing based on image profiles is implemented, then productivity and efficiency are improved, but manufacturing precision of image edits may worsen
Solution Approach 1:
All editing parameters and preferences are configured in advance and stored in the image profile before actual image processing occurs. This preliminary configuration allows the automated editing process to simply apply pre-determined settings, maintaining consistency and precision while maximizing processing speed and efficiency.
Solution Approach 2:
The system allows users to review and adjust image profiles based on their satisfaction with edited images. This feedback mechanism enables refinement of editing parameters over time, improving precision while maintaining the efficiency benefits of automation. The profile can be updated based on user feedback to achieve desired editing accuracy.
Data Source
AI summary
A method for automatically enhancing an image from a device includes obtaining a first image using an imaging device. Recognition software is configured to recognize an object or individual in the first image. An initial image profile is configured based on the first image. Editing software is used to edit at least one attribute of the initial image profile. At least one subsequent image is taken or received. The recognition software is used to recognize the object or individual in the at least one subsequent image. The at least one attribute of the at least one subsequent image is automatically edited based on the initial image profile.