Image Customization via Content-Aware Signature Analysis
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Solution Overview
Problem
Existing solutions for adjusting multimedia content, such as images, often fail to accurately and consistently account for the content features, resulting in blurry, unclear, or insufficiently bright images.
Innovation Solution
A method and system for customizing images by generating signatures representing concepts, comparing these signatures to common visual attributes from reference images, and applying customization rules based on the comparison to enhance the image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing solutions adjust images based on device orientation only, then the image orientation is corrected, but the image quality becomes blurry or unclear
Solution Approach 1:
The system changes multiple image parameters simultaneously based on content analysis. Instead of only rotating images based on device orientation, the system analyzes image content to determine appropriate adjustments in brightness, contrast, saturation, and other visual parameters, thereby improving overall image quality while maintaining correct orientation
Solution Approach 2:
The patent replaces simple mechanical rotation based on sensor data with an intelligent content-aware processing system. The system uses image analysis algorithms to understand the actual content and context of the image, then applies appropriate transformations and adjustments, substituting brute-force mechanical correction with sophisticated digital processing
2Productivity
If existing solutions apply uniform image adjustment, then the processing is simple and fast, but the results are insufficiently bright or flawed
Solution Approach 1:
The system applies different adjustment parameters to different regions or aspects of the image based on content analysis. Instead of uniform adjustment across the entire image, the system identifies specific areas requiring enhancement and applies targeted modifications to brightness, contrast, and other parameters, achieving high-quality results without sacrificing processing efficiency
Solution Approach 2:
The system performs preliminary analysis of image content before applying adjustments. By pre-processing the image to identify key features, objects, and quality issues, the system can then apply optimized adjustment parameters quickly, combining thorough analysis with fast execution through pre-computed processing strategies
3Device complexity
If existing solutions do not account for image content, then the processing is straightforward, but specific portions that should be corrected are not identified
Solution Approach 1:
The system introduces content analysis as an intermediary step between image capture and final adjustment. This intermediary layer analyzes image content to identify objects, scenes, and quality issues, then uses this information to guide subsequent processing steps, accurately identifying portions that require correction without overwhelming system complexity
Solution Approach 2:
The system implements feedback loops where image content analysis results continuously inform adjustment decisions. The system analyzes the image, applies adjustments based on content identification, evaluates the results, and refines parameters accordingly, creating a feedback-driven process that accurately identifies and corrects specific portions while maintaining manageable complexity
Data Source
AI summary
A method for customizing an image. The method includes causing generation of at least one signature for an input image, wherein each signature represents a concept, wherein each concept is a collection of signatures and metadata representing the concept; comparing the generated at least one signature to at least one signature representing at least one common visual attribute among a plurality of reference images; determining, based on the comparison, whether to customize the input image; and customizing the input image with respect to at least one of the at least one common visual attribute, when it is determined to customize the input image.