Image Processing Method for Opaque Dynamic Body Combination
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Solution Overview
Problem
Current image processing methods fail to automatically perform opaque combining of shot images, as they struggle to distinguish dynamic bodies from backgrounds, resulting in transparent dynamic bodies in combined images.
Innovation Solution
An image processing method that detects characteristic areas in multiple shot images with unique graphic patterns, generates distribution maps, and performs weighted averaging to extract and combine partial images, allowing for user-specified opacity settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If additive average combining of multiple shot images is performed, then a still background and trajectory of dynamic body are included in one image, but the dynamic body appears transparent because the background is also included in the dynamic body area
Solution Approach 1:
The patent segments the image into background areas and dynamic body areas by detecting characteristic areas in each shot image. By identifying which pixels correspond to the dynamic body versus the background, the system can separately process these regions, applying the dynamic body's image data while excluding the background, thus achieving opaque combining without manual intervention.
Solution Approach 2:
The patent extracts only the dynamic body portions from each shot image by detecting characteristic areas that differ from the averaged background. This extraction allows the system to combine only the relevant dynamic body information while discarding the background components that would cause transparency, thereby achieving reliable opaque combining.
2Reliability
If automatic detection of dynamic body presence area is attempted, then opaque combining can be realized, but it is currently difficult to detect the presence area automatically
Solution Approach 1:
The system performs self-service by automatically detecting characteristic areas through a standardized process: calculating the average image from all shot images, comparing each shot image's pixels against this average, and automatically identifying regions with significant differences as dynamic body areas. This eliminates the need for manual detection while achieving reliable opaque combining.
Solution Approach 2:
The patent changes the detection parameter from manual visual inspection to automated pixel-value comparison. By transforming the detection task into a quantitative process—comparing pixel values against an averaged reference image and applying threshold criteria—the system achieves automatic and reliable detection of dynamic body presence areas.
3Measurement precision
If characteristic area detection is performed on original-size images, then accurate detection is achieved, but processing time and computational load increase
Solution Approach 1:
The patent creates a reduced-size copy (thumbnail) of each shot image for the detection process. This copy contains sufficient characteristic information to identify dynamic body areas while requiring significantly less computational resources and time. After detection on the reduced images, the system maps the results back to the original image dimensions, achieving both speed and accuracy.
Solution Approach 2:
The patent applies partial action by performing detection only on reduced-size versions of the images rather than processing the full original images. This partial processing approach maintains sufficient detection accuracy for identifying characteristic areas while dramatically reducing processing time and computational load.
Data Source
AI summary
An image processing method of the present invention includes a detection step detecting a characteristic area from each of three or more shot images having a common graphic pattern in part thereof, the characteristic area having an image significantly different from the other shot images, and a combining step extracting a partial image located in the characteristic area from each of the three or more shot images and combining these partial images into one image.