Resource Navigation Links via Image Audio Metadata Analysis
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Solution Overview
Problem
Current search engines are inefficient in providing relevant web resource links based on input images, audio clips, or metadata, often returning thousands of irrelevant results and lacking customization options.
Innovation Solution
A system and method that processes images, audio clips, and metadata using pixel-based comparison, object recognition, and text-to-speech conversion to provide tailored resource navigation links by analyzing pixel blocks, object identification, and frequency domain transformations, allowing for precise matching and relevance determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search engines are used to search for web resource links based on input images or audio clips, then the search process is simple and fast, but the results are irrelevant and lack customization
Solution Approach 1:
The patent segments the image processing into multiple stages: extracting pixel blocks, transforming to frequency domain via DCT, comparing DCT blocks, and generating keywords. This segmentation allows complex image analysis to be broken down into manageable steps that can be processed systematically to achieve relevant search results.
Solution Approach 2:
The patent introduces an intermediary processing layer between the input image/audio and the search results. This intermediary system includes the DCT transformation layer and the keyword generation layer, which mediates between the raw input data and the final search queries, enabling relevant results to be derived from complex input media.
2Measurement precision
If image processing is performed at pixel level to find similar images, then the comparison is precise and detailed, but the processing time and computational resources increase
Solution Approach 1:
The patent segments the image into smaller pixel blocks and processes each block independently through DCT transformation. This segmentation allows parallel processing and reduces the computational complexity of comparing entire images, while maintaining precision through block-level analysis.
Solution Approach 2:
The patent transforms image data from the spatial domain (pixel values) to the frequency domain (DCT coefficients) by changing the representation parameters. This parameter transformation enables efficient comparison through frequency domain operations, reducing processing time while maintaining comparison precision.
3Measurement precision
If object recognition is performed to identify objects in images, then the content understanding is accurate, but the processing complexity and computational load increase
Solution Approach 1:
The patent replaces complex mechanical image processing operations with mathematical transformations, specifically the DCT (Discrete Cosine Transform). This substitution allows object recognition and image comparison to be performed through efficient mathematical operations in the frequency domain, reducing computational complexity while maintaining accuracy.
4Quantity of substance
If traditional search engines return thousands of results, then the search coverage is comprehensive, but the user must spend significant time filtering irrelevant results
Solution Approach 1:
The patent extracts key features from images and audio clips (such as dominant colors, patterns, and frequency characteristics) and uses these extracted features to generate precise search keywords. This extraction process filters out irrelevant information early in the process, reducing the number of results that need to be reviewed while maintaining comprehensive search coverage.
Solution Approach 2:
The system uses feedback from the image and audio analysis to dynamically generate search keywords and refine search queries. The DCT-based comparison and keyword generation create a feedback loop that adapts the search strategy based on the input media characteristics, reducing the time needed to find relevant results.
Data Source
AI summary
A system, method, and computer-readable medium, is described that implements a resource navigation links tool that receives one or more inputs, extracts information from the inputs into a submission string, submits the submission string to a resource navigation links tool, and receives resource navigation links based on the submission string. Inputs types may include images, audio clips, and metadata. The inputs sources may be processed to extract information related to the image source to build the submission string.