Image Processing System for Automated Color Adjustment
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Solution Overview
Problem
Users face challenges in efficiently extracting desired image data from large amounts of job data stored in image forming apparatuses, requiring significant time and effort for color adjustment and image formation.
Innovation Solution
A processing system that obtains first read data of a sample image, searches for similar images in stored job data, outputs a list of matching images, forms an image based on selected data, and performs color adjustment using both the first and second read data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually extract desired image data from large amounts of stored job data, then color adjustment can be performed, but significant time and effort are required
Solution Approach 1:
The system performs self-service by automatically searching and extracting similar image data from stored job data based on the target image, eliminating the need for manual extraction by users. The processing apparatus autonomously identifies and retrieves relevant historical job data that matches the current adjustment target.
Solution Approach 2:
The manual mechanical process of searching through and extracting image data is replaced by an automated information processing system. The processing apparatus uses image recognition and data matching algorithms to automatically identify and extract similar images from stored job data, substituting human manual operations with automated computational processes.
2Adaptability or versatility
If users manually search through stored job data to find similar images, then color adjustment can be performed, but the process becomes complex and time-consuming
Solution Approach 1:
The system extracts only the necessary similar image data from the large amount of stored job data using image recognition and matching algorithms. By automatically identifying and extracting relevant historical job data that matches the target image, the system simplifies the process while maintaining comprehensive color adjustment capabilities across different job types.
3Productivity
If color adjustment is performed without using historical job data, then the process is simple, but color consistency across multiple jobs cannot be achieved
Solution Approach 1:
The system implements feedback by utilizing color adjustment results from historical job data to inform and improve current color adjustment processes. By referencing previously adjusted similar images, the system creates a feedback loop that maintains color consistency across multiple jobs while improving overall adjustment efficiency through learned patterns and established color profiles.
Solution Approach 2:
The system performs preliminary action by pre-storing and organizing color adjustment data from historical jobs. When a new color adjustment task is initiated, the system has already prepared relevant historical data for quick retrieval and comparison, enabling both efficient processing and consistent results without requiring extensive real-time analysis.
Data Source
AI summary
A processing system includes a hardware processor. The hardware processor obtains first read data of a sample image for image data included in user desired job data for image formation, searches job data stored in a storage section for data of a similar image to an image included in the obtained first read data to detect the data of the similar image, outputs a list of the detected data of the similar image, causes an image forming apparatus to form an image based on selected data selected from the data included in the list, obtains second read data of the formed image, and performs color adjustment on the selected data based on the first read data and the second read data.