Signal Light Color Identification via Foreground Detection
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Solution Overview
Problem
Current light color identification methods for signal lights, such as signal machine-based and neural network-based methods, are either inconvenient due to the need for hardware modifications or require extensive data training and computation, making them inefficient for real-time applications in intelligent transportation.
Innovation Solution
A method that collects images of signal lights, determines a background image from preceding frames, and identifies moving foreground to determine the current light color without modifying the signal light or requiring large data sets, converting the light color identification problem into a foreground identification problem.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a signal machine-based identifying method is used, then light color identification can be achieved, but the signal light requires modification which is inconvenient
Solution Approach 1:
The patent uses image copying technology to capture and process visual information of the signal light. Instead of modifying the signal light hardware, the system creates digital copies (images) of the signal light and processes these copies to identify light color, thereby avoiding physical modification while maintaining identification accuracy
Solution Approach 2:
The patent replaces the mechanical/signal machine-based identification method with an image processing-based method. By substituting physical signal machine modification with digital image analysis, the system eliminates the need for hardware modification while achieving the same identification function
2Measurement precision
If a neural network-based identifying method is used, then light color identification can be achieved, but a large amount of data is required for training and the inference process is time-consuming
Solution Approach 1:
The patent extracts only the essential feature (light color information) from the image data through foreground identification, rather than using a comprehensive neural network that processes all image features. This extraction approach reduces computational complexity and inference time while maintaining identification accuracy
Solution Approach 2:
The patent applies partial action by focusing only on the necessary image processing steps (background subtraction and foreground identification) rather than applying a complete neural network training and inference pipeline. This partial processing approach reduces time consumption while achieving the required identification accuracy
Data Source
AI summary
A light color identifying method and apparatus of a signal light, and a roadside device provided in the present application relate to the field of intelligent transportation. A solution includes: collecting an image including the signal light through an image collecting apparatus; determining a background image according to N preceding frames of images of a current frame of image, where N is a positive integer greater than or equal to 1; performing foreground identification on the current frame of image according to the background image to obtain a moving foreground, where the moving foreground represents a change of the current frame of image relative to the background image; and determining, according to the moving foreground, a light color of a light that is turned on in the current frame of image.