Dynamic Image Segmentation Threshold Prediction
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Solution Overview
Problem
Existing image segmentation methods, such as thresholding, fail to accurately separate moving objects from the background in images due to their inability to account for changes in pixel intensity caused by object movement, which is crucial for applications like self-steering vehicles and missiles.
Innovation Solution
A method that dynamically adjusts and predicts a segmentation threshold by calculating a threshold factor and using a predictive filter to anticipate future average pixel intensity changes, combining these to create an adaptive threshold that accounts for object movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a static threshold is used for image segmentation, then the method is simple and fast, but the segmentation accuracy deteriorates when the object moves toward or away from the camera
Solution Approach 1:
The patent transforms the static threshold into a dynamic threshold that automatically adjusts based on object distance. The threshold value changes dynamically as the object moves toward or away from the camera, maintaining segmentation accuracy without sacrificing processing speed. This is achieved by establishing a relationship between object distance and threshold value, allowing the system to adapt to changing conditions in real-time.
Solution Approach 2:
The patent changes the threshold parameter based on object distance. By establishing a correspondence between distance parameters and threshold parameters, the system automatically selects appropriate threshold values for different object distances. This parameter transformation approach allows the threshold to adapt to motion without requiring complex recalibration or sacrificing processing efficiency.
2Ease of manufacture
If existing thresholding methods are used, then the implementation is straightforward, but the method fails to account for pixel intensity changes due to object movement
Solution Approach 1:
The patent introduces object distance as an intermediary parameter that connects the camera's perspective with the segmentation threshold. Instead of directly responding to complex pixel intensity changes, the system uses distance as a mediator to determine appropriate threshold values. This intermediary approach maintains implementation simplicity while significantly improving adaptability to object motion.
Solution Approach 2:
The patent performs preliminary calculation of the distance-threshold relationship before actual segmentation occurs. By pre-establishing the correspondence between object distance and threshold value, the system prepares the adaptive threshold in advance, making the actual segmentation process straightforward and maintaining ease of implementation while gaining motion adaptability.
Data Source
AI summary
A method of dynamically adjusting and predicting a segmentation threshold is provided. The method comprises calculating a threshold factor, calculating an actual average image pixel intensity for an entire image frame, and predicting a future average image pixel intensity for future time t, wherein the predicted future average image pixel intensity is based on past actual average image pixel intensities. The method also comprises combining the predicted future average image pixel intensity with the threshold factor to provide an adaptive threshold that adapts to changes in pixel intensity due to movement of an object in the image frame.