Image Translation Mechanism for Web Content
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
There is currently no automatic process to translate images during web content authoring, leading to images being presented in regions where they may be culturally offensive or ineffective, requiring manual determination by content authors which is prone to errors.
Innovation Solution
An image processing mechanism that identifies objects and their properties within images and generates a matrix for each language, using a trained machine learning model to determine which objects require translation, automatically determining if an image needs translation during web content authoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual determination of image translation is used by content authors, then images can be translated for different regions, but errors and cultural missteps occur due to human judgment limitations
Solution Approach 1:
The system enables images to automatically determine their own translation needs through machine learning analysis. The image translation determination mechanism autonomously analyzes image content, identifies cultural elements, and decides whether translation is required, eliminating reliance on manual human judgment and reducing errors.
Solution Approach 2:
The patent replaces the mechanical manual determination process with an automated machine learning-based system. The image translation determination mechanism uses trained models to analyze images and determine translation requirements, substituting human cognitive processes with computational algorithms for more consistent and reliable results.
2Adaptability or versatility
If no automatic image translation process is implemented, then web content authoring remains simple, but images may be culturally offensive or ineffective in different regions
Solution Approach 1:
The system performs preliminary analysis of images during the content authoring process to determine translation requirements before deployment. The image translation determination mechanism proactively identifies images that may need translation for different regions, allowing preventive adaptation rather than reactive correction.
Solution Approach 2:
The patent changes the parameter of image translation determination from manual human judgment to automated machine learning analysis. This parameter change enables the system to evaluate images based on multiple cultural parameters simultaneously, improving adaptability to different regions while maintaining automation.
3Reliability
If manual image translation determination is used, then automation level remains low, but translation errors and cultural missteps increase
Solution Approach 1:
The image translation determination mechanism implements feedback loops where the machine learning model continuously analyzes images, determines translation needs, and refines its predictions based on outcomes. This feedback system improves translation reliability over time while maintaining high productivity through automated processing.
Data Source
AI summary
Techniques and structures to facilitate conversion of a workflow process is disclosed. The techniques include receiving an image, identifying one or more objects included in the image, identifying one or more properties associated with each of the one or more objects, generating a matrix including data including the identified objects and associated properties and processing the matrix at a machine learning model to determine whether the image is to be translated based on a determination that one or more objects and associated properties within the image are required to be translated.