Image Sensor Quality Scoring Using Spatial and Frequency Analysis
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Solution Overview
Problem
Existing methods for evaluating the quality of image sensors are inefficient and time-consuming, particularly when assessing the distortion of text capture, which significantly affects user experience.
Innovation Solution
A computing device performs spatial and frequency domain analyses on captured images of neighboring lines to generate quality scores, combining local and global distortion measurements for accurate evaluation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual visual evaluation is used to assess image sensor quality, then evaluation accuracy can be achieved, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent replaces manual visual evaluation with automated computational analysis. The processor performs spatial domain analysis and frequency domain analysis (Fourier transform) on captured images to objectively measure text distortion, substituting human visual assessment with algorithmic evaluation that is both accurate and efficient.
Solution Approach 2:
The image sensor evaluation system performs self-assessment through automated analysis. The processor automatically captures test images, analyzes distortion characteristics using multiple domain approaches, and generates quality scores without requiring external manual intervention, enabling the system to evaluate itself efficiently.
2Measurement precision
If comprehensive distortion analysis is performed to accurately evaluate text capture quality, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent divides the distortion analysis into two distinct segments: spatial domain analysis and frequency domain analysis. Each domain analyzes specific aspects of text distortion independently, and their results are combined to produce a comprehensive quality score. This segmentation allows complex evaluation to be broken down into manageable, specialized analysis steps.
Solution Approach 2:
The patent transitions from single-domain analysis to multi-domain analysis by incorporating both spatial domain and frequency domain perspectives. The Fourier transform converts spatial information into frequency information, adding a new analytical dimension that reveals different distortion characteristics, thereby improving measurement precision through dimensional expansion.
Data Source
AI summary
Provided is an image sensor evaluation method using a computing device including a processor, the method including receiving, by the processor, image data obtained by capturing a plurality of neighboring lines by an image sensor, performing, by the processor, a spatial domain analysis on the image data to generate a first quality score of the image sensor, performing, by the processor, a frequency domain analysis on the image data to generate a second quality score of the image sensor, and generating, by the processor, a final quality score of the image sensor based on the first quality score and the second quality score.