Image Backlight Detection Using Block-Based Brightness Scoring
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Solution Overview
Problem
Conventional backlight detection methods fail to accurately distinguish between different light sources and intensity levels, leading to unnecessary image distortion or misrecognition in images affected by backlight, particularly from sunlight, which can compromise the reliability of autonomous driving systems.
Innovation Solution
A method and apparatus that generate brightness cumulative data based on multiple frames to detect and determine the severity of backlight images by calculating a backlight score using block regions, classifying pixels, and setting threshold values to accurately identify and classify backlight images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods uniformly determine backlight presence without considering light source type and intensity, then the detection process is simple, but the detection accuracy decreases and unnecessary image distortion occurs
Solution Approach 1:
The patent applies parameter changes by analyzing multiple parameters including brightness cumulative data, light source position, intensity distribution, and temporal characteristics to differentiate between sunlight backlight and other light sources. This enables accurate detection by considering variations in multiple parameters rather than using a uniform threshold approach
Solution Approach 2:
The patent segments the detection process into multiple stages: generating brightness cumulative data from multiple frames, identifying candidate backlight regions, calculating backlight scores based on regional distribution, and determining final backlight presence. This segmentation allows complex detection to be broken down into manageable steps while maintaining high accuracy
2Reliability
If conventional methods correct backlight images uniformly, then the correction process is simple, but image distortion increases and recognition accuracy decreases
Solution Approach 1:
The patent applies local quality by performing backlight correction on specific candidate regions identified through brightness cumulative data analysis, rather than uniformly correcting the entire image. The correction is applied selectively to regions with high backlight scores, preserving image quality in non-backlight areas while correcting distorted regions
Solution Approach 2:
The patent uses partial action by applying correction only to regions that exceed a certain backlight score threshold, rather than correcting the entire image. This partial correction approach avoids unnecessary distortion in regions without backlight while effectively correcting problematic areas
Data Source
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AI summary
An apparatus for detecting backlight of image, comprising: a processor configured to convert a pixel value for each of a plurality of image frames based on a first threshold, and block the pixel value into a plurality of block regions to generate a converted frame, generate brightness cumulative data based on the converted frame, determine a block region in which a block value is maximum in the brightness cumulative data as a backlight candidate block region, classify the block regions into first and second regions based on a position of the backlight candidate block region and calculate a backlight score using the sum of block values for the block region of the first region and the sum of block values for the block region of the second region, and determine the image as a backlight image when the backlight score based on a second threshold.