Screen Region Segmentation for Efficient Input Event Processing
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Solution Overview
Problem
Conventional image processing devices, such as network printers and MFPs, inefficiently detect user inputs by running all operational event determining routines, leading to unnecessary CPU resource occupation and decreased productivity, especially during jobs involving high-resolution image data processing.
Innovation Solution
An image processing device that classifies screen parts into closed regions capable of receiving the same event, allowing only the necessary operational event determining routine to be run based on the detected input, thereby efficiently specifying the user's input and reducing CPU load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all operational event determining routines are run one after the other to detect user input, then comprehensive gesture detection is achieved, but CPU resource occupation increases and productivity decreases
Solution Approach 1:
The screen is divided into multiple closed regions, and different sets of operational event determining routines are assigned to different regions. When a user input is detected, only the routines corresponding to the specific closed region are executed, rather than running all routines universally. This segmentation allows comprehensive gesture detection within each region while avoiding unnecessary routine execution in other regions, thus reducing CPU occupation and improving productivity.
2Adaptability or versatility
If multiple operational event determining routines are executed to specify various gestures, then gesture detection capability is enhanced, but unnecessary CPU occupation occurs when processing is not defined in certain screen parts
Solution Approach 1:
Different closed regions on the screen are assigned different qualities or capabilities - some regions support multiple gesture types while others support only specific gestures. The system executes only the operational event determining routines appropriate for the specific region where input is detected. This local quality approach ensures high adaptability and versatility for gesture detection where needed, while avoiding unnecessary CPU consumption in regions where certain gestures are not defined or supported.
3Reliability
If all operational event determining routines are run during job execution to handle user input, then complete event specification is achieved, but image processing is delayed due to CPU occupation
Solution Approach 1:
The system segments the operational event determining routines into region-specific groups. During job execution, when user input is detected, only the routines corresponding to the specific closed region are executed, rather than running all routines. This ensures reliable and accurate event specification for the detected input while minimizing CPU occupation time, thereby reducing delays in image processing and maintaining high productivity during job execution.
Data Source
AI summary
An image processing device comprises: a display part on which various types of screens are displayed; a manipulation detecting part for detecting an input by a user on the screen; a grouping part for classifying multiple screen parts contained in the screen into a group as a closed region by the screen part that is capable of receiving the same event and associating the same event with the group as the common event in the group; an event determining part for identifying the closed region where the user's input is detected and running only an operational event determining routine corresponding to the event associated with the group of the identified closed region of a plurality of operational event determining routines when the input is detected, thereby specifying the event corresponding to the user's input; and a controlling part for controlling operations based on the specified event.