一种用于复杂工业场景的相机标定方法

打开文本图片集

中图分类号：TP391.4 文献标志码：A 文章编号：2095-2945（2025）18-0071-04

Abstract：Circularpatternswithencoded informationare favoredincameracalibrationduetotheirhighaccuracyand stability.However，incomplexindustrialenvironments，calibrationboardsmayfaceisuessuchasrotationandoclusionand traditionalglobalthresholddetectionmethodsarepronetofailure，leadingtocalibrationfalures.Therefore，anewmethod combiningdeplearmingwithedgesubpixeldetectionisproposed.Thismethodfirstdetectstheminimumcircumscribedframeby rotatingtheboundingbox，thenusesaffnetransformationtoeliminateecentrcityerrors，andfinallyuseslocalthresholdsto detectedgesub-pixelstoachieveacuratecalibration.Experimentalresultsshowthattheproposedmethodismoreeficientand robust than traditional methods.

Keywords：camera calibration; coded target;rotated bounding box;deep learning;edgesubpixel detection

计算机视觉的三维测量因非接触、高精度、快速响应和强适应性而广受研究与应用[-]。（剩余4675字）