Image Processing Apparatus Single-Region Selection
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Solution Overview
Problem
Existing image processing methods require repeated operations to select multiple target regions from an image, which is inefficient.
Innovation Solution
An image processing apparatus and program that allows for a single selecting operation to identify and extract multiple target regions by displaying boundaries for candidate regions, using a processor to detect and clip foreground objects with methods like region growing and seed point setting based on user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple target regions are selected by repeating the selection operation, then each target region can be accurately identified, but the processing time and number of operations increase
Solution Approach 1:
The system performs preliminary detection of all candidate regions in the image before the user makes selections. By pre-processing the image to identify and mark all potential target regions with boundaries, the system prepares the selection interface in advance, allowing the user to efficiently select multiple regions without repeated detection operations.
Solution Approach 2:
The system creates visual copies (boundary lines) of all candidate regions simultaneously across the image. Instead of requiring sequential selection and detection, all possible target regions are copied onto the image as selectable boundaries, enabling the user to select multiple regions in a single operation pass.
2Productivity
If a single selecting operation is used to extract multiple target regions, then processing efficiency is improved, but the complexity of the selection mechanism increases
Solution Approach 1:
The system introduces boundary lines as an intermediary visual element between the image and the selection mechanism. These boundaries serve as mediators that represent candidate regions, allowing the user to interact with pre-marked regions rather than directly manipulating complex selection parameters. This intermediary layer simplifies the user interaction while enabling efficient multi-region selection.
Solution Approach 2:
The system segments the image into multiple candidate regions by drawing boundaries around potential target objects. This segmentation pre-divides the complex image into manageable, selectable units, allowing the user to efficiently select multiple discrete regions without dealing with the complexity of coordinate-based or parameter-based selection for each region individually.
3Ease of operation
If repeated selection operations are performed, then each selection can be made with full user attention, but the overall operation time and user effort increase
Solution Approach 1:
The system performs the time-consuming detection and boundary drawing operation only once before the selection phase. By preliminarily marking all candidate regions with boundaries, the system eliminates the need for repeated detection operations, allowing the user to focus solely on selection without sacrificing detection accuracy.
Solution Approach 2:
The system maintains the selected boundaries and candidate region information continuously available during the selection process. Instead of resetting or re-detecting between selections, the boundaries remain persistent, allowing the user to continuously select multiple regions without interrupting the workflow or losing previously identified candidate regions.
Data Source
AI summary
An image processing apparatus includes a processor configured to display boundaries each of which encloses a respective one of multiple candidate regions that correspond to foreground objects in an image, detect a single selecting operation, and extract a target region corresponding to one of the foreground objects from one or more candidate regions of the multiple candidate regions. The one or more candidate regions are selected by the single selecting operation.