Lane Marking Detection Using Test Zone Intensity Analysis

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Solution Overview

Problem

Existing lane detection systems in vehicles face challenges in accurately distinguishing valid lane markings from false candidates like crash barriers and tar seams, leading to impaired performance in complex traffic situations.

Innovation Solution

A method that uses an image processing system to identify and categorize detected lane markings by defining test zones and determining statistical parameters from intensity values, allowing for robust filtering and differentiation between various types of lane markings, including unbroken, broken, and invalid markings, using techniques like Hu's moments and Haar transforms.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If detection criteria are applied to identify lane markings in images, then lane marking detection is enabled, but false candidates like crash barriers and tar seams are incorrectly detected as lane markings

Engineering Contradiction:

Improvelane marking detection accuracyVSAvoidfalse positive rate

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent applies multiple image processing parameters and transformation methods (Haar transforms, Hu's moments, statistical parameters from intensity values) to characterize detected lane markings. By analyzing multiple parameters simultaneously and comparing them against expected lane marking characteristics, the system distinguishes true lane markings from false candidates like crash barriers and tar seams, thereby maintaining detection accuracy while reducing false positives

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system employs a tracking process that monitors variation over time of the course of detected lane markings. By continuously tracking and comparing lane marking positions across multiple frames, the system can identify and reject false detections that do not exhibit consistent temporal patterns, thus improving reliability without sacrificing detection capability

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If multiple lane markings are simultaneously monitored, then comprehensive lane coverage is achieved, but correct detection of all lane markings becomes difficult due to image objects meeting detection criteria that are not valid lane markings

Engineering Contradiction:

Improvemulti-lane monitoring capabilityVSAvoidlane marking detection accuracy

Core Design Contradiction:

Adaptability or versatilityVSMeasurement precision

Solution Approach 1:

The patent uses multiple characterization parameters including Haar transforms, Hu's moments, and statistical parameters from intensity values in test zones. These parameters provide distinctive signatures for different types of road markings, enabling the system to correctly identify and differentiate between multiple valid lane markings and false candidates even in complex multi-lane scenarios

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system defines test zones comprising multiple picture elements for each detected lane marking and analyzes them independently. This segmentation approach allows the system to evaluate each potential lane marking segment with multiple parameters and categorize them individually, improving the ability to correctly detect multiple lane markings while filtering out false candidates

Inventive Principle:

Principle #1Segmentation

3Reliability

If detected lane markings are categorized using image characteristics, then false candidates can be filtered out, but system complexity increases

Engineering Contradiction:

Improvefalse candidate filteringVSAvoidimage processing complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent employs multiple image processing parameters and transformation methods (Haar transforms, Hu's moments, statistical parameters from intensity values) to characterize detected lane markings. By analyzing multiple parameters simultaneously and comparing them against expected lane marking characteristics, the system distinguishes true lane markings from false candidates like crash barriers and tar seams, thereby maintaining detection accuracy while reducing false positives

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system uses a status estimator with a predictor-corrector structure to track lane markings over time. This creates a temporal model that copies and compares lane marking characteristics across multiple frames, enabling reliable distinction between valid lane markings and false candidates through temporal consistency checking without requiring overly complex single-frame analysis

Inventive Principle:

Principle #26Copying

Data Source

PatentUS9047518B2Method for the detection and tracking of lane markings

Publication Date: 2015.06.02 APTIV TECHNOLOGIES AG

AI summary

In a method for the detection and tracking of lane markings from a motor vehicle, an image of a space located in front of the vehicle is captured by means of an image capture device at regular intervals. The picture elements that meet a predetermined detection criterion are identified as detected lane markings in the captured image. At least one detected lane marking as a lane marking to be tracked is subjected to a tracking process. At least one test zone is defined for each detected lane marking. With the aid of intensity values of the picture elements associated with the test zone, at least one parameter is determined. The detected lane marking is assigned to one of several lane marking categories, depending on the parameter.