期刊文献+

基于改进滤波和标记提取的分水岭算法 被引量:28

Watershed Algorithm Based on Modified Filter and Marker-Extraction
下载PDF
导出
摘要 针对彩色图像分割中分水岭算法的过分割问题,提出了一种改进的基于标记提取的分水岭算法.改进后的算法由平滑滤波、彩色梯度计算、标记提取和分水岭变换组成.在平滑滤波阶段,设计了保边性能优于传统频域低通滤波器的频谱包络滤波器并运用于彩色图像及其梯度的平滑.彩色图像梯度计算直接在彩色向量空间进行.在标记提取阶段,利用局部极小值区的深度信息自适应控制扩展最小变换在平滑后的梯度图像中提取标记,然后融合极小值区的多重信息修改标记并将其叠加到原始梯度图像.对叠加标记后的梯度图像进行分水岭变换即得到最终的分割结果.实验结果表明,改进后的算法克服了传统算法边缘定位不准以及弱边缘提取困难等问题,参数选取更加合理,自适应程度提高. A modified marker-extraction based watershed algorithm was proposed in this paper to deal with the over-segmentation during color image segmentation.The modified algorithm was constituted of smooth filtering,color gradient calculation,marker-extraction and watershed transformation.During smooth filtering,a novel spectrum envelope filter was designed.The new filter had a better performance on edge-preserving which was used to smooth the imported color image and gradient image.The color gradient was calculated right in the color vector space.During the course of marker-extraction,H-minima transformation was used to extract minima-marker in smoothed gradient image firstly,whose parameter was adaptively controlled by the depth information of local minima region.Then,the extracted minima-marker was updated by more information of local minima region.Finally,the updated minima-marker was imposed on the original gradient image to get the marked gradient.The final result was gotten from the watershed transformation on the marked gradient.The experimental results indicate that the modified algorithm overcomes the difficulties in getting accurate edges and detecting weak edges.Furthermore,it has a more reasonable initialization rule of parameters and a better adaptability.
出处 《电子学报》 EI CAS CSCD 北大核心 2011年第4期825-830,共6页 Acta Electronica Sinica
基金 国家自然科学基金(No.60805015)
关键词 彩色图像分割 平滑滤波 分水岭 标记提取 color image segmentation smooth filtering watershed marker-extraction
  • 相关文献

参考文献11

  • 1L Vincent,et al. Watersheds in digital spaces: an efficient algorithm based on immersion simulations[ J]. 1EF.E Trans. Pattern Analysis and Machine Intelligence, 1991,13(6) :583 - 598. 被引量:1
  • 2M Femand. Topographic distance and watershed lines[ J]. Signal Processing, 1994,38(1):113 - 125. 被引量:1
  • 3P Soille. Morphological Image Analysis Principles and Applications[ M]. Berlin, Germany: Springer Verlag, 1999. 123 - 140. 被引量:1
  • 4E Bengtsson, et al. Robust cell image segmentation methods [ J]. Pattern Recogn. Image Anal, 2004,14(2) : 157 - 167. 被引量:1
  • 5高丽,杨树元,夏杰,王诗俊,梁军利,李海强.基于标记的Watershed图像分割新算法[J].电子学报,2006,34(11):2018-2023. 被引量:34
  • 6S Svensson, Aspects on the reverse fuzzy distance transform [J] .Pattern Recognition Letters,2008.29(7) :888 - 896. 被引量:1
  • 7Y Q Zhao, et al. Improved Watershed Algorithm for Dowels Image Segmentation [A ]. Proceedings of the 7th World Congress on Intelligent Control and Automation (WCICA2008) [ C]. Chongqing, China. 2008.7644 - 7648. 被引量:1
  • 8Q B Zeng, et al. Algorithm based on marker-controlled watershed transform for overlapping plant fruit segmentation[ J]. Optical Engineering, 2009,48(2) :027201 - ( 1 - 10 ). 被引量:1
  • 9冈萨雷斯,阮秋琦.数字图像处理(第二版)[M].北京:电子工业出版社,2007:97-98. 被引量:20
  • 10冈萨雷斯,等.数字图像处理[M].北京:电子工业出版社,2004.50-51. 被引量:32

二级参考文献15

  • 1Yaakov T,Amir A.Automatic segmentation of moving objects in video sequences:a region labeling approach[J].IEEE Trans on Circuits and Systems for Video Technology,2002,12(7):597-612. 被引量:1
  • 2Xu Haifeng,Akmal A Y,Mansur R K.Automatic moving object extraction for content-based applications[J].IEEE Trans on Circuits and Systems for Video Technology,2004,14(6):796-812. 被引量:1
  • 3Munchurl K,Jae G C,Daehee K,Hyung L,Myoung H L,Chieteuk A,Yo-Sung H.A VOP generation tool:automatic segmentation of moving objects in image sequences based on spatial-temporal information[J].IEEE Trans on Circuits and Systems for Video Technology,1999,9(8):1216-1226. 被引量:1
  • 4Wang Demin.Unsupervised video segmentation based on watersheds and temporal tracking[J].IEEE Trans on Circuits and Systems for Video Technology,1998,8(5):539-546. 被引量:1
  • 5Vincent L,Soille P.Watersheds in digital spaces:an efficient algorithm based on immersion simulations[J].IEEE Trans on Pattern Analysis and Machine Intelligence,1991,13(6):583-598. 被引量:1
  • 6Haris K,Efstratiadis S N,Maglaveras N,Katsaggelos A K.Hybrid image segmentation using watersheds and fast region merging[J].IEEE Trans on image processing,1998,7(12):1684-1699. 被引量:1
  • 7O'Callaghan R J Bull D R.Combined Morphological-Spectral unsupervised image segmentation[J].IEEE Trans on Image Processing,2005,14(1):49-62. 被引量:1
  • 8Paul R H,Canagarajah C N,David R B.Image segmentation using a texture gradient based watershed transform[J].IEEE Transactions on Image Processing,2003,12(12):1618-1633. 被引量:1
  • 9Gao Hai,Siu Wan-Chi,Hou Chao-Huan.Improved techniques for automatic image segmentation[J].IEEE Transactions on Circuits and Systems for video technology,2001,11(12):1273-1280. 被引量:1
  • 10Salembier P,Pardas M.Hierarchical morphological segmentation for image sequence coding[J].IEEE Trans on Image Processing,1994,3(5):639-651. 被引量:1

共引文献83

同被引文献267

引证文献28

二级引证文献210

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部