Image Processing Apparatus Selective Frame Analysis
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Solution Overview
Problem
Existing image processing technologies face inefficiencies in selecting suitable frames from moving images for still image generation, as they often require analyzing all frames, leading to increased processing load and potentially selecting less suitable frames when only some are analyzed.
Innovation Solution
An image processing apparatus and method that analyzes and evaluates frames based on predetermined feature quantities, selectively decoding and analyzing additional frames only when necessary, to ensure the selection of frames with higher evaluation scores as output targets, thereby reducing processing load while improving suitability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If all frames are analyzed and evaluated, then the quality of selected still images is improved, but the processing time increases
Solution Approach 1:
The patent applies partial action by analyzing only a subset of frames (e.g., every nth frame or frames at specific time intervals) rather than all frames. This selective analysis reduces processing time while maintaining acceptable still image quality by capturing representative moments in the moving image sequence.
Solution Approach 2:
The patent uses preliminary action by performing initial frame selection based on simple criteria (such as time intervals or keyframe detection) before conducting detailed analysis. This preliminary filtering identifies candidate frames that are likely to produce good still images, reducing the number of frames requiring full analysis.
2Loss of time
If only some frames are analyzed by sampling, then the processing time is reduced, but the suitability of selected frames for still images deteriorates
Solution Approach 1:
The patent applies feedback by using evaluation results from analyzed frames to adjust and improve the selection of subsequent frames. The system learns from the quality of selected still images and refines its frame sampling strategy, ensuring that future selections are more likely to produce suitable still images while maintaining reduced processing time.
Solution Approach 2:
The patent changes parameters such as the sampling interval, analysis depth, and evaluation criteria dynamically based on the characteristics of the moving image. By adjusting these parameters, the system optimizes the balance between processing time and still image quality for different types of video content.
3Productivity
If frames are selected by simple sampling, then the processing load is reduced, but the evaluation accuracy of frame suitability deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the frame analysis process into multiple stages: initial filtering based on simple criteria, intermediate evaluation of candidate frames, and final selection based on detailed analysis. This segmented approach reduces processing load by eliminating unsuitable frames early while maintaining evaluation accuracy through progressive refinement.
Solution Approach 2:
The patent uses dynamics by making the analysis depth and evaluation criteria adaptive based on frame characteristics. Frames that show significant changes or meet specific criteria undergo more thorough analysis, while similar or less critical frames receive lighter evaluation, optimizing both processing load and accuracy.
Data Source
AI summary
When a first frame included in a moving image satisfies a predetermined condition about a predetermined feature quantity, a second frame is analyzed and a candidate frame is selected from the first frame and the second frame as a candidate of an output target based on a result of analysis of the first frame and a result of analysis of the second frame.