Image Processing Apparatus Selective Deletion Based on Output History
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Solution Overview
Problem
Existing image processing apparatuses lack the ability to selectively delete image data based on its output history, often deleting data that may be needed again without warning or failing to delete data that is no longer necessary due to simplistic output-based deletion criteria.
Innovation Solution
An image processing apparatus with an input section, storage section, processing section, history management section, warning section, and control section that manages deletion requests based on output and input processing history, allowing for selective deletion by prompting users to perform external storage before deletion and adjusting automatic deletion conditions based on data usage patterns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If image data is deleted without exception after output, then storage space is freed efficiently, but image data that is likely to be reused is deleted causing data loss
Solution Approach 1:
The patent applies local quality by differentiating deletion policies based on the specific characteristics of each image data item. Instead of a uniform deletion approach, the system evaluates individual images' output history, input source, and reuse probability to determine whether each should be deleted or protected, thereby optimizing both storage utilization and data protection on a per-item basis.
Solution Approach 2:
The patent implements dynamics by making the deletion decision process adaptive rather than static. The system continuously monitors image data usage patterns, output history, and source information to dynamically adjust which images are eligible for deletion. This dynamic evaluation ensures that deletion policies adapt to actual user behavior and data importance, preventing premature deletion of valuable images while freeing space for less critical ones.
2Reliability
If image data is protected from deletion, then data loss is prevented, but storage space is wasted by retaining unnecessary data
Solution Approach 1:
The patent applies local quality by differentiating deletion policies based on the specific characteristics of each image data item. Instead of a uniform deletion approach, the system evaluates individual images' output history, input source, and reuse probability to determine whether each should be deleted or protected, thereby optimizing both storage utilization and data protection on a per-item basis.
Solution Approach 2:
The patent implements parameter changes by using multiple evaluation criteria (output history, input source, reuse probability) to dynamically adjust the protection status of image data. By changing these parameters and their weights, the system can flexibly control which images are protected and which are eligible for deletion, balancing data protection needs with storage efficiency.
3Ease of operation
If deletion decisions are based solely on output status, then processing is simple and fast, but accuracy in determining deletable data is low
Solution Approach 1:
The patent applies segmentation by breaking down the deletion decision process into multiple independent evaluation dimensions: output history analysis, input source identification, and reuse probability assessment. Each dimension is evaluated separately and then integrated to form a comprehensive deletion decision, allowing the system to maintain processing efficiency while improving decision accuracy through structured multi-criteria evaluation.
Solution Approach 2:
The patent implements feedback by continuously monitoring image data usage patterns and output history, then using this information to refine deletion decisions. The system learns from actual user behavior and adjusts its evaluation criteria accordingly, improving the accuracy of deletion decisions over time while maintaining a relatively simple processing framework through iterative optimization.
Data Source
AI summary
An image processing apparatus having: an image data inputting section; a storage section that stores image data that has been input from the inputting section; a processing section that carries out output processing of the image data; a history management section that establishes correspondence between history information of the output processing and the image data and manages the history information; a warning section; and a control section that, in response to a deleting request for the image data stored in the storage section, based on the history information of the output processing, changes a mode of the warning given out by the warning section of confirming the deleting of the image data.