Touching Particles Separation Based on Area Ratio of Circular Mask
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- 英文论文题名：Touching Particles Separation Based on Area Ratio of Circular Mask
- 论文作者：Wencheng Wang ; Xiaohui Yuan ; Shuhong Tang
- 英文论文作者：Wencheng Wang ; Xiaohui Yuan ; Shuhong Tang ; College of Information and Control Engineering ; Weifang University ; Harbin Institute of Technology
- 年：2017
- 作者机构：College of Information and Control Engineering,Weifang University;Harbin Institute of Technology;
- 英文论文关键词：Circular mask ; area ratio ; touching particles ; gray projection
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（B）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
- 语种：英文
- 分类号：TP391.41
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：4
- 文件大小：200k
- 原文格式：D
- 会议级别：全国
摘要
In this paper,a method for separation of partially overlapping particle is proposed based on circular mask,and the framework including image segmentation,concave points detection,point pair matching and shape estimation is realized.First,the color image is preprocessed to obtain a binary image.Then,the corner detection algorithm is adopted to achieve rough estimation on potential concave points,and the area ratio method was used to select the candidate points so as to obtain the segmentation points.Since then,the obtained segmentation points are matched to each pairs by gray projection according to a certain criteria.Finally,each pair of points and one of their adjacent pixels on the border is used to estimate the status of individual particles before adhesion,and the contour of each particle is outputted.Experiments show that the proposed method is consistent with the human visual perception,and has achieved good results
In this paper,a method for separation of partially overlapping particle is proposed based on circular mask,and the framework including image segmentation,concave points detection,point pair matching and shape estimation is realized.First,the color image is preprocessed to obtain a binary image.Then,the corner detection algorithm is adopted to achieve rough estimation on potential concave points,and the area ratio method was used to select the candidate points so as to obtain the segmentation points.Since then,the obtained segmentation points are matched to each pairs by gray projection according to a certain criteria.Finally,each pair of points and one of their adjacent pixels on the border is used to estimate the status of individual particles before adhesion,and the contour of each particle is outputted.Experiments show that the proposed method is consistent with the human visual perception,and has achieved good results
In this paper,a method for separation of partially overlapping particle is proposed based on circular mask,and the framework including image segmentation,concave points detection,point pair matching and shape estimation is realized.First,the color image is preprocessed to obtain a binary image.Then,the corner detection algorithm is adopted to achieve rough estimation on potential concave points,and the area ratio method was used to select the candidate points so as to obtain the segmentation points.Since then,the obtained segmentation points are matched to each pairs by gray projection according to a certain criteria.Finally,each pair of points and one of their adjacent pixels on the border is used to estimate the status of individual particles before adhesion,and the contour of each particle is outputted.Experiments show that the proposed method is consistent with the human visual perception,and has achieved good results
引文
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[8]S.Nazlibilek,D.Karacor,T.Ercan,M.H.Sazli,O.Kalender,Y.Ege,Automatic segmentation,counting,size determination and classification of white blood cells,Measurement,55:58-65,2014.
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[12]X.Bai,C.Sun,F.Zhou,Splitting touching cells based on concave points and ellipse fitting,Pattern Recognition,42(11):2434-2446,2009.
[13]X.He,N.Yung,Curvature scale space corner detector with adaptive threshold and dynamic region of support,IEEE Proceedings of the 17th International Conference on Pattern Recognition,2004:791-794.
[14]J.Huang,An improved algorithm of overlapping cell division,Proceedings of the 2010 International Conference on Intelligent Computing and Integrated Systems,2010:687-691.
[15]J.Cheng,J.Rajapakse,Segmentation of clustered nuclei with shape markers and marking function,IEEE Transactions on Biomedical Engineering,56(3):741-748,2009.
[16]C.Jung,C.Kim,Segmenting clustered nuclei using H-minima transform-based marker extraction and contour parameterization,IEEE Transactions on Biomedical Engineering,57(10):2600-2604,2010.
[17]R.Fu,H.Shen,H.Chen,Research of automatically separating algorithm for overlap cell based on searching concave spot,Computer Engineering and Application,43(17):21-23,2007.
[2]H.Yang,N.Ahuja,Automatic segmentation of granular objects in images:Combining local density clustering and gradient-barrier watershed,Pattern Recognition,47(6):2266-2279,2014.
[3]C.D.Ruberto,A.Dempster,S.Khan,B.Jarra,Analysis of infected blood cell images using morphological operators,Image and Vision Computing,20(2):133-146,2002.
[4]M.Farhan,O.Yli-Harja,A.Niemist?,A novel method for splitting clumps of convex objects incorporating image intensity and using rectangular window-based concavity point-pair search,Pattern Recognition,46(3):741-751,2013.
[5]M.Plissiti,C.Nikou,Overlapping cell nuclei segmentation using a spatially adaptive active physical model,IEEE Transactions on Image Processing,21(11):4568-4580,2012.
[6]Z.Lu,G.Carneiro,A.P.Bradley,An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cells,IEEE Transactions on Image Processing,24(4):1261-1272,2015.
[7]N.Kharma,H.Moghnieh,J.Yao,Y.P.Guo,A.Abu-Baker,J.Laganiere,G.Rouleau,M.Cheriet,Automatic segmentation of cells from microscopic imagery using ellipse detection,IET Image Processing,1(1):39-47,2007.
[8]S.Nazlibilek,D.Karacor,T.Ercan,M.H.Sazli,O.Kalender,Y.Ege,Automatic segmentation,counting,size determination and classification of white blood cells,Measurement,55:58-65,2014.
[9]S.Kumar,S.H.Ong,S.Ranganath,T.C.Ong,F.T.Chew,A rule-based approach for robust clump splitting,Pattern Recognition,39(6):1088-1098,2006.
[10]G.Diaz,F.Gonzalez,E.Romero,Automatic clump splitting for cell quantification in microscopical images,Progress in Pattern Recognition,Image Analysis and Applications,pp.763-772,2007.
[11]A.LaTorre,L.Alonso-Nanclares,S.Muelas,J.M.Pena,J.DeFelipe,Segmentation of neuronal nuclei based on clump splitting and a two-step binarization of images,Expert Systems with Applications,40(16):6521-6530,2013.
[12]X.Bai,C.Sun,F.Zhou,Splitting touching cells based on concave points and ellipse fitting,Pattern Recognition,42(11):2434-2446,2009.
[13]X.He,N.Yung,Curvature scale space corner detector with adaptive threshold and dynamic region of support,IEEE Proceedings of the 17th International Conference on Pattern Recognition,2004:791-794.
[14]J.Huang,An improved algorithm of overlapping cell division,Proceedings of the 2010 International Conference on Intelligent Computing and Integrated Systems,2010:687-691.
[15]J.Cheng,J.Rajapakse,Segmentation of clustered nuclei with shape markers and marking function,IEEE Transactions on Biomedical Engineering,56(3):741-748,2009.
[16]C.Jung,C.Kim,Segmenting clustered nuclei using H-minima transform-based marker extraction and contour parameterization,IEEE Transactions on Biomedical Engineering,57(10):2600-2604,2010.
[17]R.Fu,H.Shen,H.Chen,Research of automatically separating algorithm for overlap cell based on searching concave spot,Computer Engineering and Application,43(17):21-23,2007.