Printed Image Reading Feedback to Prevent Repeat Scan Failures
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users may mistakenly fail to read images from printed matter, leading to repeated failures in subsequent attempts, as seen in techniques like JP2004-139603A, without adequate support for improving reading operations.
Innovation Solution
An image analysis apparatus and method that analyzes read images from printed matter to provide support information, including advice on reading and image capturing methods, and executes image corrections based on analysis results, utilizing machine learning for user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If image data of read images is used without analysis, then the reading operation is simple and quick, but the user may mistakenly execute reading operations and fail to read the image, leading to repeated failures
Solution Approach 1:
The system performs preliminary analysis of the read image to generate support information before the user completes the reading operation. This includes analyzing image quality, detecting reading errors, and preparing correction suggestions in advance, so that when the user encounters reading failures, the support information is already ready to guide corrective actions, preventing repeated failures while maintaining quick reading speed
Solution Approach 2:
The system implements a feedback mechanism where the analysis result of the read image is used to generate support information that is fed back to the user. This feedback loop allows the system to learn from reading errors and provide targeted guidance, improving the user's reading operations over time while maintaining efficient reading throughput
2Reliability
If support information is provided based on comprehensive analysis, then the user receives accurate reading and capturing advice, but the analysis complexity and processing time increase
Solution Approach 1:
The analysis process is segmented into multiple independent modules: image quality analysis, reading error detection, capturing method analysis, and support information generation. Each module handles a specific aspect of the analysis independently, which reduces the complexity of the overall system while maintaining comprehensive analysis capability. The segmented approach allows parallel processing and reduces bottlenecks
Solution Approach 2:
The analysis system is designed with multi-functional capabilities that can handle various types of analysis (image quality, reading errors, capturing methods) using a unified framework. This universal approach reduces redundancy and simplifies the system architecture while providing comprehensive support information across different analysis dimensions
Data Source
AI summary
Provided are an image analysis apparatus, an image analysis system, an image analysis method, a program, and a recording medium for supporting a user who reads a printed matter and uses data of a read image.An image analysis apparatus includes a processor, in which the processor executes a process of reading a printed matter on which a captured image is printed to acquire image data of a read image, a process of analyzing a first content related to reading of the printed matter based on the image data, and a process of acquiring first support information based on an analysis result of the first content.