Proactive Image Analysis via Quality Assessment and Metadata
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image analysis tools on mobile devices struggle to provide accurate results due to limitations in capturing high-quality image data, leading to difficulties in conventional extraction techniques like OCR, especially under varying conditions.
Innovation Solution
A computer-implemented method that proactively improves image analysis by generating or retrieving analysis information based on the suitability of image data and metadata, allowing for accurate analysis even when image quality is insufficient, by evaluating conditions and generating metadata for image analysis and processing requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional extraction techniques like OCR are used on mobile device images, then text recognition can be achieved, but accurate results cannot be obtained due to insufficient image quality
Solution Approach 1:
The patent introduces an image quality assessment intermediary that evaluates whether captured images meet quality thresholds before processing. When quality is insufficient, the system mediates by selecting alternative extraction techniques or requesting additional images, thereby resolving the contradiction between maintaining accuracy and dealing with poor quality inputs from mobile devices
Solution Approach 2:
The system dynamically changes processing parameters based on image quality assessment. When image quality is poor, it adjusts extraction parameters, switches to alternative techniques, or modifies processing thresholds to maintain text recognition accuracy despite degraded input conditions
2Measurement precision
If high-quality image data is required for accurate analysis, then analysis accuracy improves, but computational costs and network traffic increase
Solution Approach 1:
The system performs preliminary image quality assessment before committing to full analysis processing. By evaluating quality metrics in advance, it can determine whether high-quality analysis is even necessary, avoiding unnecessary computational expenditure on images that would yield poor results anyway
Solution Approach 2:
The patent applies partial processing based on quality assessment. For images of sufficient quality, full analysis is performed; for borderline cases, partial processing or alternative techniques are used; for poor quality images, minimal processing or rejection occurs. This prevents excessive computational action on unsuitable inputs
3Measurement precision
If multiple images are captured to ensure sufficient quality, then analysis accuracy improves, but time consumption increases
Solution Approach 1:
The system implements feedback-based quality control where each captured image is immediately assessed. Based on the assessment feedback, the system determines whether to proceed with analysis or capture additional images. This closed-loop approach minimizes unnecessary captures while ensuring quality requirements are met
Solution Approach 2:
Quality assessment is performed preliminarily on each captured image before analysis processing. This preliminary evaluation enables immediate determination of whether the image meets quality thresholds, avoiding time-wasting processing of poor quality images and reducing the need for multiple capture attempts
Data Source
AI summary
Systems, methods, and computer program products for proactively improving image analysis and/or processing in real time are presented, in accordance with various embodiments. In one embodiment, a computer-implemented method includes: receiving an analysis and/or processing request from a mobile device; and either generating or retrieving analysis and/or processing information based on a result of either or both of: determining whether the analysis and/or processing request includes image data suitable for generating an analysis and/or processing result; and determining whether the analysis and/or processing request includes metadata suitable for generating an estimated analysis and/or processing result. In another embodiment, a computer-implemented method includes: capturing image data; evaluating one or more conditions corresponding to the captured image data; generating metadata corresponding to the captured image data; and generating and submitting the analysis and/or processing request to an analysis and/or processing platform. Corresponding systems and computer program products are also described.