UI Digital Asset Placement Analysis via Image Scanning
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Solution Overview
Problem
Current methods for determining the placement of digital assets on user interfaces across different platforms are inefficient and impractical, often requiring manual data collection or HTML parsing that lacks scalability and accuracy, especially when access to published HTML is restricted.
Innovation Solution
A method and system that uses image scanning and processing by electronic devices to capture and analyze user interface data, identifying digital asset parameters and position information without user involvement or direct HTML access, employing AI for reliable and scalable compliance checking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If crowd sourcing approach is used to collect user interface data, then user involvement is obtained, but scalability and data quality are compromised
Solution Approach 1:
The electronic device automatically performs UI scanning and data collection without requiring user action. The device's processor captures screenshots and extracts asset placement information autonomously, eliminating the need for users to manually navigate and capture screenshots while maintaining high scalability across multiple devices.
Solution Approach 2:
The manual mechanical process of users capturing screenshots is replaced with an automated electronic system. The device uses its camera or display buffer to capture UI images, then uses image processing algorithms to automatically extract asset placement data, replacing the mechanical human action with an electronic automation system.
2Productivity
If HTML parsing approach is used to access user interface data, then data access efficiency is improved, but accessibility to electronic devices is limited
Solution Approach 1:
Instead of directly accessing HTML code, the system uses screenshot images as an intermediary representation of the UI. The image processing system extracts asset placement information from these visual representations, allowing any electronic device with a display to be analyzed regardless of whether it provides HTML access.
Solution Approach 2:
The system creates a visual copy of the UI through screenshots rather than accessing the source HTML code. This copied visual representation can be processed by any electronic device, making the approach universally applicable across different platforms and devices that may or may not provide HTML access.
3Measurement precision
If manual data collection is conducted to ensure data quality, then accuracy is improved, but time consumption increases
Solution Approach 1:
The system performs continuous automated scanning and data extraction without interruption. The processor continuously captures UI images and processes them to extract asset placement information, eliminating the intermittent manual collection process while maintaining high accuracy through algorithmic consistency.
Solution Approach 2:
Manual data collection processes are replaced with automated image processing algorithms. The system uses computer vision and pattern recognition to automatically identify and extract asset placement information from screenshots, replacing time-consuming manual analysis with rapid automated processing that maintains high accuracy.
Data Source
AI summary
A method, carried out by one or more processors, for analysing the placement in a user interface, by an electronic device, of digital assets, the method comprising scanning image data of a user interface of an electronic device, capturing image data of an instance of the user interface of the electronic device, identifying a parameter of one or more digital assets in the captured image data.