TY - GEN
T1 - A Fast Adaptive Subpixel Extraction Method for Light Stripe Center
AU - Zou, Wei
AU - Wei, Zhenzhong
N1 - Publisher Copyright:
© 2019, Springer Nature Switzerland AG.
PY - 2019
Y1 - 2019
N2 - Aiming at the problem of light stripe distribution uneven and large curvature variation, which results in wrong stripe center extraction, a fast light stripe center extraction method based on the adaptive template is proposed. Firstly, the adaptive threshold method is used to reduce the image convolution area, and the multi-thread parallel operation is used to improve the speed of extracting the light stripe center. Secondly, the multi-direction template method is used to estimate the width of the light stripe along the normal direction, so that the size of the Gaussian template can be automatically obtained. Finally, the Hessian matrix eigenvalues are normalized to eliminate the multiple light stripe centers at both ends of the light stripe, and avoid extracting the wrong light stripe centers at the intersection position or the large curvature change, thus ensuring the continuity of the light stripe. This method has fast processing speed, good robustness, and high precision. It is very suitable for vision measurement image, medical image, and remote sensing image.
AB - Aiming at the problem of light stripe distribution uneven and large curvature variation, which results in wrong stripe center extraction, a fast light stripe center extraction method based on the adaptive template is proposed. Firstly, the adaptive threshold method is used to reduce the image convolution area, and the multi-thread parallel operation is used to improve the speed of extracting the light stripe center. Secondly, the multi-direction template method is used to estimate the width of the light stripe along the normal direction, so that the size of the Gaussian template can be automatically obtained. Finally, the Hessian matrix eigenvalues are normalized to eliminate the multiple light stripe centers at both ends of the light stripe, and avoid extracting the wrong light stripe centers at the intersection position or the large curvature change, thus ensuring the continuity of the light stripe. This method has fast processing speed, good robustness, and high precision. It is very suitable for vision measurement image, medical image, and remote sensing image.
KW - Gussian filter
KW - Hessian matrix
KW - Image extraction
KW - Light stripe center
KW - Normalization
UR - https://www.scopus.com/pages/publications/85076903834
U2 - 10.1007/978-3-030-34120-6_64
DO - 10.1007/978-3-030-34120-6_64
M3 - 会议稿件
AN - SCOPUS:85076903834
SN - 9783030341190
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 785
EP - 800
BT - Image and Graphics - 10th International Conference, ICIG 2019, Proceedings, Part 1
A2 - Zhao, Yao
A2 - Lin, Chunyu
A2 - Barnes, Nick
A2 - Chen, Baoquan
A2 - Westermann, Rüdiger
A2 - Kong, Xiangwei
PB - Springer
T2 - 10th International Conference on Image and Graphics, ICIG 2019
Y2 - 23 August 2019 through 25 August 2019
ER -