Traffic Line Recognition via 3D Coordinate Histogram Projection
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Solution Overview
Problem
Conventional traffic line recognition devices require high-performance processing units and large resources, making them costly and unsuitable for vehicle-mounted applications, especially when dealing with different types of traffic lines like white lines and Botts' dots.
Innovation Solution
A traffic line recognition device that converts two-dimensional image coordinates of traffic line region candidates into three-dimensional coordinates and produces a histogram by projecting these coordinates across the road, allowing for traffic line determination without the need for high-performance processing or extensive resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Hough transformation is used to find white lines on road, then traffic line recognition capability is improved, but processing load increases requiring high-performance processing units
Solution Approach 1:
The patent segments the traffic line recognition task into distinct phases: candidate region extraction based on color/position, followed by classification of specific line types (white lines, Botts' dots, etc.). This segmentation allows each phase to use optimized, simpler algorithms rather than requiring a single high-performance Hough transformation approach for all line types.
Solution Approach 2:
The patent changes the processing parameters by working with image coordinate data and classification criteria rather than applying computationally intensive Hough transformation. It uses parameters like color characteristics, position, and shape features to classify traffic lines, which requires lower processing power while maintaining recognition accuracy.
2Adaptability or versatility
If different processing methods are used for white lines and Botts' dots, then adaptability to different traffic line types is improved, but resource consumption increases
Solution Approach 1:
The patent implements a universal classification framework that handles multiple traffic line types (white lines, Botts' dots, yellow lines, etc.) through a single integrated system. The classification unit uses a set of classification criteria that can identify and distinguish various line types without requiring separate dedicated processing systems for each type, thereby reducing memory resources while maintaining versatility.
3Measurement precision
If high-performance processing units and large resources are used, then traffic line recognition accuracy is improved, but device cost increases
Solution Approach 1:
The patent employs inexpensive image processing techniques and classification algorithms that can be implemented on low-cost hardware. Instead of relying on expensive high-performance processing units, it uses simpler image analysis methods with classification criteria that achieve sufficient recognition accuracy for vehicle-mounted applications, thereby reducing device cost while maintaining functional effectiveness.
Data Source
AI summary
A traffic line recognition device includes: a traffic line region candidate extraction section that extracts a traffic line candidate, as a traffic line candidate, from a road image obtained by a TV camera installed on a vehicle; a two dimension/three dimension transform section that transforms two dimensional image coordinates of a pixel contained in the traffic line region candidate into three dimensional coordinates; a histogram production section that accumulates and projects the three dimensional coordinates onto a coordinate system in a direction crossing a road and produces a histogram in the direction crossing the road; and a traffic line judgment unit determines a traffic line based on that histogram.