Interface-Guided Diffusion Backgrounds for UI Element Visibility

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Solution Overview

Problem

Conventional browser applications face limitations in customization, particularly when incorporating generative machine-learning images as backgrounds, which can obscure user interface elements, making them difficult to discover, especially for visually impaired users.

Innovation Solution

An interface-guided diffusion model generates UI-compatible output images based on user-generated text and layout information, ensuring the images enhance discoverability of UI elements by accounting for their positions, sizes, and colors, including monochromatic schemes for colorblind users.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If generative machine-learning images are used as backgrounds, then customization is improved, but UI element discoverability deteriorates

Engineering Contradiction:

ImprovecustomizationVSAvoidUI element discoverability

Core Design Contradiction:

Adaptability or versatilityVSDifficulty of detecting and measuring

Solution Approach 1:

The image generation process is segmented into multiple passes: first generating the background image, then detecting UI element locations, and finally modifying the image in regions corresponding to UI elements to ensure they remain discoverable. This segmentation allows the system to balance customization with UI element visibility.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies different quality requirements to different regions of the background image. Regions corresponding to UI elements are modified to maintain their discoverability, while other regions preserve the full customization potential. This local quality approach ensures UI elements remain detectable without sacrificing overall customization.

Inventive Principle:

Principle #3Local quality

2Difficulty of detecting and measuring

If complex image processing is applied to ensure UI element visibility, then UI element discoverability is improved, but computational complexity increases

Engineering Contradiction:

ImproveUI element discoverabilityVSAvoidcomputational complexity

Core Design Contradiction:

Difficulty of detecting and measuringVSDevice complexity

Solution Approach 1:

The system performs preliminary detection of UI element locations before finalizing the background image. By identifying where UI elements will be placed and pre-modifying the background image in those regions, the system avoids more complex post-processing and reduces overall computational complexity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary step that detects UI element locations and uses this information to guide the image modification process. This intermediary detection mechanism simplifies the overall complexity by providing structured information about where modifications are needed, rather than attempting complex global optimization.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12469185B2Application customization using an interface-guided diffusion model

Publication Date: 2025.11.11 GOOGLE LLC

AI summary

According to an aspect, a method may include generating, by an interface-guided diffusion model, a UI-compatible output image in response to one or more prompts including user-generated text and input condition data. The input condition data includes user interface (UI) layout information about at least one UI element included in an interface of an application. The method includes providing the UI-compatible output image to the application.