|
|
Outline Extraction of Bundled Logs Cross Section Based on Multi-feature |
JING Lin,LIN Yao-hai,HUANG Xi-pei |
School of Computer Science and Technology, Fujian Agriculture and Forest University, Fuzhou, Fujian 350002, China |
|
|
Abstract A model of outline extraction of bundled logs cross section based upon pixel feature and edge structure is developed to improve bundled logs image processing. A support vector machine (SVM) is used to extract the pixels of cross section of logs, and the least square method is applied to fit the circle of edge pixels. Finally, outlines of bundled logs are extracted. The obtained results of experiment demonstrate the validity of the proposed method in the case of the cross section of logs is not the ideal smooth and the background is complex.
|
|
|
|
|
[1]Kass M, Witkin A, Terzopoulos D. Snakes: Active contour models[J]. International journal of computer vision, 1988, 1(4): 321-331.
[2]Xu C, Prince J L. Snakes, shapes and gradient vector flow[J]. IEEE Transactions on Image Processing, 1998, 7(3): 359-369.
[3]Li C, Xu C, Gui C, et al. Level set evolution without re-initialization: a new variational formulation [C] // Computer Vision and Pattern Recognition, San Diego, CA, USA, 2005: 430-436.
[4]Rochery M, Jermyn I H, Zerubia J. Higher order active contours[J]. International Journal of Computer Vision, 2006, 69(1): 27-42.
[5]Horvath P, Jermyn I H, Kato Z, et al. A higher-order active contour model 1of a ‘gas of circles’ and its application to tree crown extraction [J]. Pattern Recognition, 2009, 42(5): 699-709.
[6]Li C, Kao C Y, Gore J C, et al. Minimization of region-scalable fitting energy for image segmentation[J]. IEEE Transactions on Image Processing, 2008, 17(10): 1940-1949.
[7]Zhu G, Zhang S, Zeng Q, et al. Gradient vector flow active contours with prior directional information[J]. Pattern Recognition Letters, 2010, 31(9): 845-856.
[8]Chung K L, Huang Y H. Speed up the computation of randomized algorithms for detecting lines, circles, and ellipses using novel tuning-and LUT-based voting platform[J]. Applied Mathematics and Computation, 2007, 190(1): 132-149.
[9]吴凤和.基于计算机视觉测量技术的图像轮廓提取方法研究[J].计量学报, 2007, 28(1):18-22.
[10]栾新, 朱铁一. 长堆积原木材积的自动检测[J].计算机应用与软件, 1999, 16(6):61-64.
[11]景林, 黄习培.成捆原木计算机图像检尺系统研究及应用[J].计算机应用, 2006, 26(12z):137-139.
[12]梅振荣, 任洪娥, 朱朦.基于非线性最小二乘原理的原木端面识别算法[J].计算机工程与应用, 2012, 48(2):177-178.
[13]樊尚春, 龙德帆, 庞宏冰. 原木材积自动化检测系统[J].中国造纸, 2003, 22(3):27-29.
[14]龙德帆, 樊尚春, 庞宏冰.用于原木材积检测的图像处理与分析算法[J].北京航空航天大学学报, 2005, 31(1):82-85.
[15]景林, 林耀海, 温永仙, 等.结合色彩特征和空域特征的成捆原木轮廓识别[J].计算机系统应用, 2013, 22(7):196-199.
[16]黄习培, 景林.原木端面图像检尺直径识别算法的研究[J].林业机械与木工设备, 2006, 34(1): 24-26. |
|
|
|