Traffic Light Image Processing for Oversaturation Correction

The patent segments the traffic light detection process into multiple stages: initial detection stage (short exposure) and detailed identification stage (long exposure). By dividing the imaging process into different exposure time segments, the system can detect traffic light status with short exposure to avoid oversaturation, then use long exposure separately for clear vehicle information capture, resolving the contradiction between traffic light reliability and vehicle information identification.

The patent introduces an intermediary verification mechanism using multiple color space transformations (RGB, HSV, LAB) and multiple hypothesis testing. Instead of directly identifying traffic light color from a single image, the system uses color temperature analysis and temporal sequence verification as intermediaries to distinguish oversaturated red light from yellow light, significantly improving measurement precision while maintaining detection capability.

The patent implements a feedback-based correction system that continuously monitors detection results and adjusts correction parameters accordingly. The system uses temporal sequence feedback to verify whether correction operations are appropriate, and employs confidence threshold feedback to determine when correction is needed. This feedback mechanism prevents erroneous correction of red lights mistaken for yellow lights, maintaining high detection accuracy while enabling automated color correction.

The patent applies partial action by selectively processing only the abnormal regions of the image rather than the entire image. The system first identifies small abnormal pixel regions using simple thresholding, then applies complex correction algorithms only to these limited areas. This approach maintains real-time processing capability while achieving accurate color correction where needed, resolving the contradiction between automated correction and real-time speed.