Arrow Signal Recognition Device Distance-Based Pixel Filtering
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Solution Overview
Problem
Existing arrow signal recognition systems face challenges in accurately detecting arrow signal lights from a distance, particularly with light bulb traffic lights, due to varying luminance and color tone inconsistencies, leading to decreased recognition precision.
Innovation Solution
An arrow signal recognition device that includes an onboard camera, an image recognition processor, and an arrow signal detector with modules for setting arrow signal areas, searching for color tone effective and ineffective pixels, and calculating effective pixel numbers to determine the presence of arrow signal lights based on distance and luminance thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If a low color feature amount threshold is set to detect arrow signal lights from afar, then the detection range is extended, but the precision of recognition decreases
Solution Approach 1:
The patent segments the detection process into multiple stages: first identifying candidate pixels based on color tone, then filtering them through spatial relationship checks and luminance ratio checks. This multi-stage segmentation allows the system to maintain high precision while detecting arrows at greater distances, resolving the contradiction between extended detection range and recognition precision.
Solution Approach 2:
The patent applies different detection criteria to different spatial locations within the arrow signal light. By checking luminance ratios between center and peripheral pixels, the system adapts the detection threshold locally according to the expected luminance distribution pattern, maintaining precision across varying distances without requiring a uniformly low threshold.
2Measurement precision
If a high color feature amount threshold is set to maintain recognition precision, then the precision of recognition is improved, but the detection range is limited
Solution Approach 1:
The patent dynamically adjusts the effective pixel count threshold based on the detected arrow distance. As distance increases, the system allows for a lower minimum pixel count threshold, accommodating the reduced image resolution at longer ranges while maintaining precision through the spatial relationship verification that confirms the detected pixels form a valid arrow pattern.
3Adaptability or versatility
If conventional extraction methods are used for light bulb traffic lights, then the system works for LED traffic lights, but recognition becomes difficult from afar due to varying luminance
Solution Approach 1:
The patent changes the detection parameters from fixed color feature amount thresholds to dynamic thresholds based on spatial relationships and luminance ratios. This allows the system to adapt to both LED and light bulb traffic light characteristics, maintaining precision at various distances by adjusting to the different luminance distribution patterns of each type.
Data Source
AI summary
Based on an image captured by an onboard camera, an arrow signal detector sets an arrow signal area on the basis of a signal light distance between a lit red signal light of a traffic light and a vehicle equipped with the arrow signal recognition device, counts the number of color tone effective pixels assumed as being lit within each arrow signal area, further searches for and counts color tone ineffective pixels in the color tone effective pixels on the basis of pixel information on the vicinity of each color tone effective pixel, and calculates an arrow effective pixel number from the difference between the number of color tone effective pixels and the number of color tone ineffective pixels.