A novel feature-based tracking approach to the detection, localization, and 3-D reconstruction of internal defects in hardwood logs using computer tomography

التفاصيل البيبلوغرافية
العنوان: A novel feature-based tracking approach to the detection, localization, and 3-D reconstruction of internal defects in hardwood logs using computer tomography
المؤلفون: Richard L. Daniels, E. William Tollner, Xingzhi Luo, Suchendra M. Bhandarkar
المصدر: Pattern Analysis and Applications. 9:155-175
بيانات النشر: Springer Science and Business Media LLC, 2006.
سنة النشر: 2006
مصطلحات موضوعية: business.industry, Computer science, Image segmentation, Kalman filter, Tracking (particle physics), Edge detection, Artificial Intelligence, Feature (computer vision), Nondestructive testing, Pattern recognition (psychology), Computer vision, Computer Vision and Pattern Recognition, Artificial intelligence, Tomography, business
الوصف: A novel feature-based tracking approach based on the Kalman filter is proposed for the detection, localization, and 3-D reconstruction of internal defects in hardwood logs from cross-sectional computer tomography (CT) images. The defects are simultaneously detected, classified, localized, and reconstructed in 3-D space, making the proposed scheme computationally much more efficient than existing methods where the defects are detected and localized independently in individual CT image slices and the 3-D reconstruction of the defects accomplished via correspondence analysis across the various CT image slices. Robust techniques for defect detection and classification are proposed. Defect class-specific tracking schemes based on the Kalman filter, B-spline contour approximation, and Snakes contour fitting are designed which use the geometric parameters of the defect contours as the tracking variables. Experimental results on cross-sectional CT images of hardwood logs from select species such as white ash, hard maple, and red oak are presented.
تدمد: 1433-755X
1433-7541
DOI: 10.1007/s10044-006-0035-9
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::02ca6ff4695f7ae9876365b387236140
https://doi.org/10.1007/s10044-006-0035-9
Rights: CLOSED
رقم الانضمام: edsair.doi...........02ca6ff4695f7ae9876365b387236140
قاعدة البيانات: OpenAIRE
الوصف
تدمد:1433755X
14337541
DOI:10.1007/s10044-006-0035-9