Road Sign Recognition via Spatial Zone Prediction
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Solution Overview
Problem
Current road sign recognition systems require high computing effort and suffer from insufficient robustness due to the need to search the entire image for potential road signs, which increases processing time and reduces accuracy.
Innovation Solution
The method determines relevant spatial zones in the camera's field of view based on known object positions and road course, calculates image zones on the image plane, and predicts the size of objects within these zones using camera parameters, allowing for focused search areas and reduced computing time while enhancing robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire image is searched for potential road signs using feature extraction and classification, then comprehensive detection is achieved, but computing effort and computing time increase significantly
Solution Approach 1:
The image is divided into multiple zones based on spatial probability, with only high-probability zones subjected to full feature extraction and classification. This segmentation approach maintains detection completeness in critical areas while reducing overall computing effort by excluding low-probability regions from intensive processing.
Solution Approach 2:
Different processing qualities are applied to different image regions: high-probability zones receive full classification and feature extraction, while low-probability zones receive reduced or no processing. This local quality differentiation optimizes the balance between detection reliability and computing efficiency.
2Measurement precision
If feature extraction and classification are performed on all image candidates, then accurate road sign identification is achieved, but computing time increases
Solution Approach 1:
Spatial probability zones are pre-calculated based on road geometry and camera parameters before actual road sign detection. This preliminary action enables the system to quickly identify which regions warrant full classification processing, thereby reducing overall processing time while maintaining accuracy in high-probability areas.
Solution Approach 2:
Full feature extraction and classification are applied only to high-probability zones rather than the entire image. This partial action approach achieves sufficient recognition accuracy for critical regions while significantly reducing computing time by excluding low-probability areas from intensive processing.
3Reliability
If the search area covers the entire field of view, then no road signs are missed, but the computing effort increases
Solution Approach 1:
The field of view is segmented into high-probability and low-probability zones based on spatial reasoning about road geometry and typical road sign locations. This segmentation allows the system to focus computational resources on high-probability zones, reducing overall computational complexity while maintaining robustness through comprehensive coverage of critical areas.
Solution Approach 2:
The system dynamically adjusts the search strategy by changing the effective search parameter (processing intensity) based on spatial probability. High-probability zones receive full processing with all feature extraction and classification, while low-probability zones receive reduced processing, thereby reducing computational complexity while maintaining detection robustness.
Data Source
AI summary
The invention relates to a method for the prediction of the size to be expected of the image of a stationary object associated with a road in a picture of the environment in the field of view of a camera device which is in particular arranged at a motor vehicle and which has an image plane including image elements, wherein at least one relevant spatial zone from the field of view of the camera device is determined; wherein boundaries of the calculated projection onto the image plane of the at least one relevant spatial zone are determined in order to determine at least one relevant image zone; wherein a directional beam is determined for each of the image elements in the at least one relevant image zone, said directional beam including those spatial points from the field of view which would be projected onto the respective image element on a projection onto the image plane; and wherein at least one value for the size to be expected of the image of a road sign in the respective image element is determined for each of the image elements in the relevant image zone.