Lane Line Detection Model Brightness Preprocessing
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Solution Overview
Problem
Current lane line detection methods face difficulties in accurately detecting lane lines in backlit road images due to high brightness, which affects driving safety.
Innovation Solution
The method involves an electronic device that performs image processing on road images, including lane line detection, perspective transformation, histogram equalization, and binarization, to reduce the influence of image brightness and enhance lane line recognition. This involves obtaining road images, identifying a region of interest, transforming it to a bird's-eye view, applying histogram equalization, and binarization, and inputting the processed area into a trained lane line detection model for accurate feature extraction and prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional lane line detection methods are used on backlit road images, then the detection process is simple, but the lane lines become blurred and detection accuracy deteriorates due to high brightness
Solution Approach 1:
The patent applies image preprocessing operations (histogram equalization, binarization, and region of interest extraction) before lane line detection to mitigate the harmful effects of high brightness. By performing these preliminary actions on the backlit road images, the patent enhances the contrast and clarity of lane lines before the actual detection process, thereby improving detection accuracy without requiring complex detection algorithms.
2Measurement precision
If image preprocessing operations are applied to reduce brightness impact, then lane line recognition improves, but processing complexity increases
Solution Approach 1:
The patent segments the image processing task into distinct stages: histogram equalization to adjust brightness distribution, binarization to separate lane lines from background, and region of interest extraction to focus on relevant areas. This segmentation of the processing pipeline allows each operation to be optimized independently and reduces overall complexity compared to applying a single complex processing method to the entire image.
Data Source
AI summary
A method for detecting lane lines, applied in an electronic device, includes: obtaining road images, and obtaining a splice area by performing an image processing on the road images; inputting the splice area into a preset trained lane line detection model and obtaining lane line detection images; and obtaining transformed images and lane line detection results of the transformed images by performing an image transformation on the lane line detection images. The application is able to improve an accuracy of detecting lane lines.