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  • Distortion Calibration Charts

USAF1951 Test Target

Traditional checkerboard squares replaced with AprilTag coded labels while retaining corner detection characteristics. Can complete missing information through corner topological relationships when some tags are occluded. Primarily applied in single-camera high-precision intrinsic parameter and distortion calibration, especially suitable for industrial vision, AR/VR, binocular stereo vision, and other scenarios requiring pixel-level precision.
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ISO12233 Test Target

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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IEEE Test Target

Utilizes correspondence between geometric centers of circles and 3D world coordinates to solve camera intrinsic, extrinsic, and distortion parameters. More suitable for high-precision positioning scenarios compared to checkerboards. Commonly used for semiconductor wafer inspection camera calibration, distortion correction in microscopy imaging systems, and joint calibration of LiDAR and cameras in autonomous driving.

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Halcon Circle/Dot Pattern

Utilizes correspondence between geometric centers of circles and 3D world coordinates to solve camera intrinsic, extrinsic, and distortion parameters. More suitable for high-precision positioning scenarios compared to checkerboards. Commonly used for semiconductor wafer inspection camera calibration, distortion correction in microscopy imaging systems, and joint calibration of LiDAR and cameras in autonomous driving.

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Kalibr/AprilGrid

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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Kalibr/AprilGrid

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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SFR Test Targets

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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Ronchi Ruling Test Targets

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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  • Distortion Calibration Charts

ChArUco

Traditional checkerboard squares replaced with AprilTag coded labels while retaining corner detection characteristics. Can complete missing information through corner topological relationships when some tags are occluded. Primarily applied in single-camera high-precision intrinsic parameter and distortion calibration, especially suitable for industrial vision, AR/VR, binocular stereo vision, and other scenarios requiring pixel-level precision.
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Kalibr/AprilGrid

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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Checkboard OpenCV

Utilizes correspondence between geometric centers of circles and 3D world coordinates to solve camera intrinsic, extrinsic, and distortion parameters. More suitable for high-precision positioning scenarios compared to checkerboards. Commonly used for semiconductor wafer inspection camera calibration, distortion correction in microscopy imaging systems, and joint calibration of LiDAR and cameras in autonomous driving.

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Halcon Circle/Dot Pattern

Utilizes correspondence between geometric centers of circles and 3D world coordinates to solve camera intrinsic, extrinsic, and distortion parameters. More suitable for high-precision positioning scenarios compared to checkerboards. Commonly used for semiconductor wafer inspection camera calibration, distortion correction in microscopy imaging systems, and joint calibration of LiDAR and cameras in autonomous driving.

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Concentric Circles/Squares

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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  • Distortion Calibration Charts

DOF Test Chart

Traditional checkerboard squares replaced with AprilTag coded labels while retaining corner detection characteristics. Can complete missing information through corner topological relationships when some tags are occluded. Primarily applied in single-camera high-precision intrinsic parameter and distortion calibration, especially suitable for industrial vision, AR/VR, binocular stereo vision, and other scenarios requiring pixel-level precision.
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Gray Scale

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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Gray Reflectance

Utilizes correspondence between geometric centers of circles and 3D world coordinates to solve camera intrinsic, extrinsic, and distortion parameters. More suitable for high-precision positioning scenarios compared to checkerboards. Commonly used for semiconductor wafer inspection camera calibration, distortion correction in microscopy imaging systems, and joint calibration of LiDAR and cameras in autonomous driving.

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24-Color Standard Chart

Utilizes correspondence between geometric centers of circles and 3D world coordinates to solve camera intrinsic, extrinsic, and distortion parameters. More suitable for high-precision positioning scenarios compared to checkerboards. Commonly used for semiconductor wafer inspection camera calibration, distortion correction in microscopy imaging systems, and joint calibration of LiDAR and cameras in autonomous driving.

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Concentric Circle Reticle

Technically can infer global coordinates through spatial relationships of remaining tags even when partially occluded. Coded information recognition makes calibration process automated, especially suitable for complex systems requiring fusion of camera, IMU, LiDAR, and other multi-source data. In autonomous driving, UAVs, medical equipment, and other scenarios with stringent precision and real-time requirements, AprilGrid has become the standard solution for multi-sensor calibration.
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Model Material Coating Type Over size Target Type Thickness Pattern
LTU-025-(0-9,1)-PG Quartz Glass Blue Chrome 25 x 25mm 1" x 1'' Positive 1.6mm Group 0 Element1 to Group 9 Element 1
LTU-025-(0-9,1)-NG Quartz Glass Blue Chrome 25 x 25mm 1" x 1'' Negative 1.6mm Group 0 Element1 to Group 9 Element 1
LTU-025-(0-9,6)-PG Quartz Glass Blue Chrome 25 x 25mm 1" x 1'' Positive 1.6mm Group 0 Element 1 to Group 9 Element 6
LTU-025-(0-9,6)-PG Quartz Glass Blue Chrome 25 x 25mm 1" x 1'' Negative 1.6mm Group 0 Element 1 to Group 9 Element 6
LTU-050-(0-9,1)-PG Quartz Glass Blue Chrome 50 x 50mm 2" x 2'' Positive 1.6mm Group 0 Element1 to Group 9 Element 1
LTU-050-(0-9,1)-PG Quartz Glass Blue Chrome 50 x 50mm 2" x 2'' Negative 1.6mm Group 0 Element1 to Group 9 Element 1
LTU-050-(0-9,6)-PG Quartz Glass Blue Chrome 50 x 50mm 2" x 2'' Positive 1.6mm Group 0 Element1 to Group 9 Element 6
LTU-050-(0-9,6)-PG Quartz Glass Blue Chrome 50 x 50mm 2" x 2'' Negative 1.6mm Group 0 Element1 to Group 9 Element 6
LTU-076-(-2-9,1)-PG Quartz Glass Blue Chrome 76 x 76mm 3" x 3'' Positive 1.6mm Group -2 Element1 to Group 9 Element 1
LTU-076-(-2-9,1)-PG Quartz Glass Blue Chrome 76 x 76mm 3" x 3'' Negative 1.6mm Group -2 Element1 to Group 9 Element 1
LTU-076-(-2-9,6)-PG Quartz Glass Blue Chrome 76 x 76mm 3" x 3'' Positive 1.6mm Group -2 Element1 to Group 9 Element 6
LTU-076-(-2-9,6)-PG Quartz Glass Blue Chrome 76 x 76mm 3" x 3'' Negative 1.6mm Group -2 Element1 to Group 9 Element 6
Model NO. Substrate Material Coating Type Overall Target Size Active Pattern Area Checkerboard Pattern Array Feature Accuracy Add to Cart
LTO-030-2.0-G Soda Lime Glass Brown Chrome 30 x 30mm
1.2‘’ x 1.2'' 		26 x 24mm
1.0'' x 0.94'' 		2.0 x 2.0mm 13 x 12 1μm
LTO-045-3.0-G Soda Lime Glass Brown Chrome 45 x 45mm
1.8‘’ x 1.8'' 		39 x 36mm
1.5'' x 1.4'' 		3.0 x 3.0mm 13 x 12 1μm
LTO-060-4.0-G Soda Lime Glass Brown Chrome 60 x 60mm
2.4‘’ x 2.4'' 		52 x 48mm
2.0'' x 1.9'' 		4.0 x 4.0mm 13 x 12 1μm
LTO-76-5.0-G Soda Lime Glass Brown Chrome 76 x 70mm
3.0‘’ x 2.8'' 		65 x 60mm
2.6'' x 2.4'' 		5.0 x 5.0mm 13 x 12 1μm
LTO-88-6.0-G Soda Lime Glass Brown Chrome 88 x 88mm
3.5‘’ x 3.5'' 		78 x 72mm
3.1'' x 2.8'' 		6.0 x 6.0mm 13 x 12 1μm
LTO-111-8.0-G Soda Lime Glass Brown Chrome 111 x 106mm
4.4‘’ x 4.2'' 		104 x 96mm
4.1'' x 3.8'' 		8.0 x 8.0mm 13 x 12 1μm
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