Personalized Image Enhancement Profiles for Automated Attribute Editing
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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, tattoos, 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, tattoos, or advertisements based on user preferences, and transferring these edited images across different devices and platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual image editing is performed for each image, then image enhancement quality is improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs preliminary actions by creating enhancement profiles based on user preferences in advance. These profiles store predefined enhancement parameters and settings that are automatically applied to subsequent images, eliminating the need for manual editing of each image while maintaining consistent enhancement quality.
Solution Approach 2:
The system enables self-service automation where the image enhancement process operates autonomously once profiles are established. The automated enhancement system applies stored profiles to images without requiring continuous user intervention, reducing time consumption while preserving enhancement quality through consistent application of predefined parameters.
2Productivity
If automated image enhancement is implemented, then processing speed is improved, but personalization capability deteriorates
Solution Approach 1:
The system applies local quality by creating customized enhancement profiles for different users, objects, or image types. Each profile contains specific enhancement parameters tailored to particular needs (e.g., different filters for portraits vs. landscapes, different attribute enhancements for different individuals), allowing automated processing to maintain high personalization capability while achieving fast processing speeds.
Solution Approach 2:
The system utilizes parameter changes by storing multiple enhancement profiles with different parameter sets that can be automatically selected and applied. This allows the automated system to adapt to various personalization requirements by changing enhancement parameters based on the specific image or user preferences, maintaining both speed and personalization.
3Speed
If image profiles are stored locally on devices, then access speed is improved, but device storage requirements increase
Solution Approach 1:
The system segments image profiles into smaller, modular components that can be selectively stored and transferred. Instead of storing complete profile datasets locally, the system divides profiles into essential elements that can be kept on-device for quick access while allowing selective transfer to other devices, reducing local storage requirements while maintaining access speed for frequently used enhancements.
4Measurement precision
If recognition software processes every image attribute, then enhancement accuracy is improved, but computing burden increases
Solution Approach 1:
The system extracts and processes only the specific image attributes that are relevant to the user's enhancement goals rather than analyzing every attribute in the image. By identifying and isolating only the necessary features (e.g., skin tone, facial structure, specific objects) based on the enhancement profile, the system achieves high enhancement accuracy while significantly reducing the computing burden compared to comprehensive image analysis.
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.