Automated Image Quality Assurance Filter System
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Solution Overview
Problem
Existing digital content platforms face challenges in ensuring the appropriateness of images published on their platforms for association with third-party content, such as advertisements, as inappropriate images can negatively impact brand reputation and require manual filtering, which is inefficient and scalable.
Innovation Solution
A computer-implemented system and method for analyzing images using a quality assurance filter and image-content matching engine to assess appropriateness, involving hash-based, content-based, and relationship-based filters, and a crowdsource network for contextual analysis, ensuring only suitable images are linked with advertisements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual filtering is used to identify inappropriate images, then image appropriateness can be assessed, but the process is inefficient and not scalable
Solution Approach 1:
The patent replaces manual mechanical filtering with automated computer-implemented systems including hash-based filters, content-based filters, and relationship-based filters. These electronic systems process images through algorithmic analysis rather than human review, dramatically increasing throughput while maintaining assessment quality.
Solution Approach 2:
The system enables images to self-identify their content characteristics through hash generation and automatic tagging. Images are processed through filters that autonomously determine appropriateness without human intervention, with the system serving itself through automated decision-making algorithms.
2Reliability
If multiple filtering mechanisms are implemented to ensure image quality, then image appropriateness is improved, but system complexity increases
Solution Approach 1:
The patent divides the filtering system into distinct modular components: hash-based filters for quick identification, content-based filters for detailed analysis, and relationship-based filters for contextual assessment. Each filter operates independently and can be configured separately, managing complexity through functional segmentation.
Solution Approach 2:
The system introduces intermediary elements such as hash values and metadata tags that mediate between raw images and final appropriateness decisions. These intermediaries simplify the filtering process by providing structured data that filters can process efficiently without direct complex image analysis.
3Productivity
If automated filtering systems are used to process images at scale, then productivity increases, but measurement precision of image content may deteriorate
Solution Approach 1:
The system performs preliminary hash-based filtering and metadata extraction before detailed content analysis. This preliminary action pre-processes images to identify obvious cases quickly, allowing the system to allocate more computational resources to complex cases that require higher measurement precision.
Solution Approach 2:
The patent applies multiple layers of filtering where some filters perform partial analysis and others perform excessive or redundant analysis on the same content. This ensures that even if one filter misses nuances, other filters compensate, maintaining precision while processing large volumes through parallel partial assessments.
Data Source
AI summary
Disclosed herein are computer-implement systems and methods for identifying and analyzing content (e.g., text, images, videos, etc.) published on digital content platforms (e.g., webpages, mobile applications, etc.). Such analysis is then used to determine whether the published content is appropriate for association with (or “hosting of”) a third-party's content. In one embodiment, for example, the systems and methods presented are particularly useful for determining the appropriateness of an image published on a digital content platform, prior to providing an advertisement proximate the image. As such, merchants can avoid associating their advertised products/services with vulgar, obscene, or otherwise inappropriate images that may have a negative impact on their brand or reputation.