Smartphone Image Quality Scoring for Automated Document Capture
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for automating the processing of images, such as proof of purchases, face challenges due to the need for precise human intervention to digitize and highlight relevant information, leading to inefficiencies and reliance on human resources for validation, especially when dealing with complex or low-quality images.
Innovation Solution
A method for producing a reliable dematerialized image using a smartphone device that acquires a stream of images, evaluates their quality in real-time, and automatically adjusts settings to ensure the image meets predetermined criteria for automated processing, including geometric and qualitative evaluations, ensuring the image is suitable for automated processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human resources are used to manually validate and process proof of purchases, then processing accuracy is improved, but productivity is reduced and reliance on human resources increases
Solution Approach 1:
The system performs self-validation through automated image quality assessment and geometric verification algorithms. The device automatically evaluates captured images against predefined criteria (geometric scores, qualitative scores) and prompts users to retake images only when necessary, eliminating the need for manual human validation of each proof of purchase.
Solution Approach 2:
Manual human validation is replaced by an automated digital system that uses image processing algorithms, geometric analysis, and quality scoring mechanisms. The system substitutes human cognitive processing with computational algorithms that evaluate image characteristics and determine acceptability automatically.
2Manufacturing precision
If dedicated physical means are deployed for image acquisition, then image quality is improved, but device complexity and deployment cost increase
Solution Approach 1:
The system uses a universal smartphone device with integrated camera and processing capabilities that can handle multiple functions (image capture, quality assessment, geometric verification, and validation) in one device. This eliminates the need for dedicated specialized hardware while maintaining image quality requirements through software-based quality control.
Solution Approach 2:
The system implements real-time feedback loops where image quality metrics (geometric scores, qualitative scores) are continuously evaluated during capture. Based on this feedback, the system provides immediate guidance to users for improving image quality or automatically determines acceptability, ensuring high-quality images without complex dedicated equipment.
3Reliability
If real-time image evaluation and automatic adjustments are implemented, then processing reliability is improved, but use of energy and computational resources increase
Solution Approach 1:
The system performs partial evaluation by focusing computational resources on key quality metrics (geometric scores, qualitative scores) rather than analyzing every aspect of the image in full detail. This selective approach maintains processing reliability while reducing overall computational energy consumption compared to exhaustive image analysis.
Data Source
Figure 1~3
Figure 2
AI summary
The method involves acquiring a flow of images (1010), and calculating an image score of one of the images based on basic scores (1020). The image score is memorized, and time during which the images remain continuously above a preset threshold is evaluated (1110). The time is compared to preset duration. The image corresponding to last calculated score is automatically recorded and image acquisition is stopped if the time is greater than preset threshold. An image score improvement command is produced (1100) according to the basic scores if the time is less than the preset threshold. Independent claims are also included for the following: (1) a computer program product comprising sequence of instructions executable by an information processing unit to implement a method for producing images (2) a user terminal product to implement a method for producing images.