Image Processing Apparatus AF Target Selection via Detection Area Segmentation
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Solution Overview
Problem
Existing image capturing systems face difficulties in focusing on small or fast-moving objects due to the challenge of maintaining overlap between the object detection frame and the fixed AF frame, leading to issues in selecting the desired object as the AF target.
Innovation Solution
An image processing apparatus that detects objects and sets relevant areas, allowing the user to easily select the AF target by determining overlap between the search area and the detection area, and prioritizing higher-order parts of the detected object for focus, thus enabling easier capture within the fixed AF frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the object detection frame is made smaller to improve detection precision for small objects, then the overlap between the detection frame and fixed AF frame becomes more difficult to maintain, but this makes it harder to select the desired object as the AF target
Solution Approach 1:
The patent segments the detection area into multiple zones: a first detection area (smaller, higher precision) and a second detection area (larger, easier to overlap with AF frame). By dividing the detection function across different area sizes, the system maintains both precision for small objects and ease of target selection through the larger second detection area that is easier to overlap with the fixed AF frame.
2Ease of operation
If the detection frame is expanded to make it easier to overlap with the fixed AF frame, then the ease of selecting AF target improves, but the detection precision for small objects deteriorates
Solution Approach 1:
The detection area is segmented into a first detection area for precise small object detection and a second detection area for easier overlap with the AF frame. This segmentation allows each zone to serve its specific function optimally without compromising the other.
Solution Approach 2:
Different regions of the detection area are assigned different qualities: the first detection area maintains smaller dimensions for precision, while the second detection area is larger for ease of overlap. This local differentiation in area size allows the system to simultaneously achieve both precision and ease of operation in different spatial zones.
3Reliability
If multiple detection areas are set to accommodate both precision and overlap requirements, then the system complexity increases, but this enables better handling of small and fast-moving objects
Solution Approach 1:
The detection area is divided into structured segments (first and second detection areas) with defined relationships. This segmentation provides a systematic approach to managing multiple areas, reducing the complexity that would otherwise arise from unstructured multi-area management.
Solution Approach 2:
The system preliminarily sets both the first and second detection areas based on object characteristics before the focusing operation. By pre-configuring the appropriate detection areas according to object size and movement characteristics, the system avoids complex real-time adjustments during operation, thereby managing complexity while maintaining reliability.
Data Source
AI summary
An image processing apparatus configured to process a captured image includes a detection unit configured to detect an object from the image and to acquire first and second detection areas, a relevant area setting unit configured to set the first detection area as a relevant area relevant to the second detection area, a search area setting unit configured to set a search area related to the object in the image, and a target setting unit configured to set an arbitrary area in the image as a target area for processing, wherein, in a case where the search area and the second detection area or the relevant area overlap, the target setting unit sets the second detection area as the target area, and wherein the detection unit detects a train as the object and acquires the first and second detection areas.