Zobrazeno 1 - 10
of 1 012
pro vyhledávání: '"contour extraction"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Aiming at the problem that the edge artifacts of Si3N4 ceramic bearing rolling element microcracks have low contrast, contain noise, and easily merge with the background, making it difficult to segment. A method based on 2D discrete wavelet
Externí odkaz:
https://doaj.org/article/d17bad3616f3492a90d30b931a29a86b
Publikováno v:
Современные инновации, системы и технологии, Vol 4, Iss 4 (2024)
Contour extraction is a core task in computer vision, serving as the foundation for object detection, segmentation, and scene understanding across various applications, including autonomous vehicles, medical imaging, and industrial automation. This p
Externí odkaz:
https://doaj.org/article/2fc24cfb725c43208f63dc3ba3714e5a
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 133, Iss , Pp 104126- (2024)
Extracting buildings from True Digital Ortho Maps often encounters occlusions and misidentifications, making it challenging to obtain complete, regular, and accurate building contours. To address this issue, we developed a building recognition proces
Externí odkaz:
https://doaj.org/article/c2f7a55f765543ed8cab73afa0aaeef1
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 16316-16328 (2024)
Building roof contours are important geometric features of the building and play an important role in the fields of three-dimensional model reconstruction and target detection. Due to the uneven density of the airborne light detection and ranging poi
Externí odkaz:
https://doaj.org/article/a040b6e945a44e61ac6dd6fd9916ffb5
Autor:
Zuoping Tan, Xuan Chen, Qiang Xu, Can Yang, Xiaomin Lin, Yan Huo, Mohammad Alzogool, Riwei Wang, Yan Wang
Publikováno v:
BioMedical Engineering OnLine, Vol 23, Iss 1, Pp 1-14 (2024)
Abstract Background In this study, an automatic corneal contour extraction algorithm with a shared model is developed to extract contours from dynamic corneal videos containing noise, which improves the accuracy of corneal biomechanical evaluation an
Externí odkaz:
https://doaj.org/article/857cb6470a054caaa0ceb8e03a2f83e2
Publikováno v:
Remote Sensing, Vol 16, Iss 19, p 3669 (2024)
Ship contour extraction is vital for extracting the geometric features of ships, providing comprehensive information essential for ship recognition. The main factors affecting the contour extraction performance are speckle noise and amplitude inhomog
Externí odkaz:
https://doaj.org/article/29c22613b3604bfdafa0ef2bfadb1fbc
Publikováno v:
Aircraft Engineering and Aerospace Technology, 2023, Vol. 95, Issue 8, pp. 1217-1226.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/AEAT-11-2022-0331
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
In this paper, an automatic building extraction process based on MVS point clouds is proposed to automatically extract building point clouds from urban MVS dense point clouds of complex scenes by projection, morphological expansion and contour extrac
Externí odkaz:
https://doaj.org/article/26066f9a568147b2aabf8e5e8b8f816b
Autor:
Yufeng He, Xiaobian Wu, Weibin Pan, Hui Chen, Songshan Zhou, Shaohua Lei, Xiaoran Gong, Hanzeyu Xu, Yehua Sheng
Publikováno v:
Remote Sensing, Vol 16, Iss 13, p 2404 (2024)
Oblique photography is a regional digital surface model generation technique that can be widely used for building 3D model construction. However, due to the lack of geometric and semantic information about the building, these models make it difficult
Externí odkaz:
https://doaj.org/article/ac01398f8c024cc7bf60278cf36be33a
Publikováno v:
Remote Sensing, Vol 16, Iss 1, p 190 (2024)
Because of the complex structure and different shapes of building contours, the uneven density distribution of airborne LiDAR point clouds, and occlusion, existing building contour extraction algorithms are subject to such problems as poor robustness
Externí odkaz:
https://doaj.org/article/9414b1ed5ebf4076addc9bcafb121a81