基于视差信息的立体图像主动闭合轮廓提取算法研究

任慧; 苏志斌; 高楠; 吕朝辉

doi:10.11999/JEIT170496

基于视差信息的立体图像主动闭合轮廓提取算法研究

doi: 10.11999/JEIT170496

基金项目:

国家科技支撑计划项目(2012BAH01F04)，校级工科规划项目(3132016XNG1622)

计量
- 文章访问数: 1441
- HTML全文浏览量: 176
- PDF下载量: 170
- 被引次数: 0
出版历程
- 收稿日期: 2017-05-24
- 修回日期: 2017-10-16
- 刊出日期: 2018-02-19

Extraction Algorithm for Active Contour Based on Disparity Information of Stereoscopic Image

Funds:

The National Science and Technology Planning Project (2012BAH01F04), The Research Project of Communication University of China (3132016XNG1622)

摘要

摘要: 针对立体图像中目标对象的闭合轮廓提取任务，该文提出一种基于视差信息的轮廓提取算法。该算法在传统贪婪蛇模型的基础上，利用各控制点和中心的视差关系为模型设计收缩和膨胀力，能够有效指导初始轮廓曲线向目标边缘的收敛。同时算法采用重复利用经处理的控制点作为模型输入的循环迭代方式，能够获得分布均匀且较为密集的边缘曲线。实验结果表明，该轮廓提取算法减少了传统的贪婪蛇模型算法对初始值的依赖，准确度和可靠性均得到了很大的提升。
- 闭合轮廓提取 /
- 视差信息 /
- 贪婪蛇 /
- 初始轮廓
Abstract: To get the closed boundary of target object of given stereoscopic image, this paper proposes an improved algorithm with disparity-guided constraint for active contour extraction based on greedy snake model. The disparity relationship between the control points and the center of the object is used to design a new external force, which guides the original contour to real boundary. In addition, this method also uses the improved model iteratively with processed control points as the original input. Experiment results prove this method reduces the reliance on initial values of input contour, obtains accurate contour made up of uniform and dense points, which is more effective than the traditional greedy snake algorithm.
- Closed contour extraction /
- Disparity information /
- Greedy snake /
- Original contour

HTML全文

参考文献(24)

谢昭, 童昊浩, 孙永宣, 等. 一种仿生物视觉感知的视频轮廓检测方法[J]. 自动化学报, 2015, 41(10): 1814-1824. doi: 10.10383./j.aas.2015.c150018.

XIE Zhao, TONG Haohao, SUN Yongxuan, et al. Video contour detection method based on bionic visual perception[J]. Journal of Automation, 2015, 41(10): 1814-1824. doi: 10.10383/j.aas.2015.c150018.

尹辉, 王鹏飞, 黄华, 等. 基于全局运动对比度的轮廓编组元提取算法[J]. 计算机工程与应用, 2016, 52(9): 184-189.

YIN Hui, WANG Pengfei, HANG Hua, et al. Extraction algorithm of contour marshalling unit based on global motion contrast[J]. Computer Engineering and Applications, 2016, 52(9): 184-189.

KASS Michael, WITKIN Andrew, and TERZOPOULOS Demetri. Snakes: Active contour model[J]. International Journal of Computer Vision, 1988, 1(4): 321-331.

IlUNGA-MBUYAMBA E, CRUZ-DUARTE J M, AVINA- CERVANTES J G, et al. Active contours driven by Cuckoo Search strategy for brain tumour images segmentation[J]. Expert Systems with Applications, 2016, 56: 59-68. doi: 10.1016/j.eswa.2016.02.048.

董恩增, 冯倩, 于晓, 等. 基于主动轮廓模型的红外图像轮廓提取算法[J]. 激光与红外, 2017, 47(3): 379-384. doi: 10.3969/ j.issn.1001-5078.2017.03.024.

DONG Enzeng, FENG Qian, YU Xiao, et al. Infrared image contour extraction algorithm based on active contour model [J]. Laser and Infrared, 2017, 47(3): 379-384. doi: 10.3969/ j.issn.1001-5078.2017.03.024.

LI Yan, LUO Siwei, and ZOU Qi. Active contour model based on salient boundary point image for object contour detection in natural image[J]. IEICE Transactions on Information and System, 2010, E93, D(11): 3136-3139. doi: 10.1587/transinf. E93.D.3136.

CIECHOLEWSKI Marcin. An edge-based active contour model using an inflation/deflation force with a damping coefficient[J]. Expert Systems with Applications, 2015, 44(C): 22-36. doi: 10.1016/j.eswa.2015.09.013

涂松, 李禹, 粟毅. 基于主动轮廓模型的SAR图像分割方法综述[J]. 系统工程与电子技术, 2015, 37(8): 1754-1766.

TU Song, LI Yu, and LI Yi. Overview of SAR image segmentation based on active contour model[J]. Systems Engineering and Electronics, 2015, 37(8): 1754-1766.

KHUNTETA A and GHOSH D. Object boundary detection using active contour model via multiswarm PSO with fuzzy- rule based adaptation of inertia factor[J]. Advances in Fuzzy Systems, 2016: 6179576. doi: 10.1155/2016/6179576.

娄联堂, 丁明跃, 周成平. 基于量子力学目标轮廓提取方法[J].计算机工程与应用, 2005, 41(31): 94-97.

LOU Liantang, DING Mingyue, and ZHOU Chengping. Target contour extraction method based on quantum mechanics[J]. Computer Engineering and Applications, 2005, 41(31): 94-97.

SANG H K, KIM J Y, and SO G J. Object extraction with excessive disparities in 3D stereoscopic images[J]. International Journal of Computer Theory and Engineering, 2014, 6(4): 313-318.

JU Ran, REN Tongwei, and WU Gangshan. StereoSnakes: Contour based consistent object extraction for stereo images[C]. Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile, 2015: 1724-1732. doi: 10.1109/ICCV.2015.201.

WILLIAMS D J and SHAH M. A fast algorithm for active contours and curvature estimation[J]. CVGIP: Image Understanding, 1992, 55(1): 14-26. doi: 10.1016/1049-9660 (92)90003-L.

CASELLES V, CATTE F, COLL T, et al. A geometric model for active contours in image processing[J]. Numerische Mathematik, 1993, 66(1): 1-31. doi: 10.1007/BF01385685.

张荣国, 刘焜, 蔡江辉, 等. 变形曲线曲面主动轮廓模型方法[M]. 北京: 国防工业出版社, 2012: 52-56.

张辉, 吴月宁. 一种改进的Snake模型图像分割算法[J]. 微型机与应用, 2010, 29(11): 36-37.

ZHANG Hui and WU Yuening. An improved image segmentation algorithm based on Snake model[J]. Microcomputer and Application, 2010, 29(11): 36-37.

DEEPAK R, NAYAK A V, and MANIKANTAN K. Ear detection using active contour model[C]. International Conference on Emerging Trends in Engineering, Pattaya, Thailand, 2016: 1-7. doi: 10.1109/ICETETS.2016.7603043.

REN Hui, SU Zhibin, L? Chaohui, et al. An improved algorithm for active contour extraction based on greedy snake[C]. IEEE/ACIS International Conference on Computer Information Science, Las Vegas, USA, 2015: 589-592. doi: 10.1109/ICIS.2015.7166662.

施引文献

资源附件(0)

访问统计