A Modified Segmentation Approach for Overlapping Elliptical Objects with Various Sizes

Segmentation of elliptical objects has many real-world applications including morphology analysis on biological cell, material particles and other objects which need quantitative analysis according to size and shape. However, overlapping and varying in size may make the objects segmentation extremely challenging. In this paper, a modified segmentation approach for overlapping objects with different sizes is proposed. Specifically, we extract all the concave points for each connected region from the object’s silhouette. We next fit all of the circles by two adjacent concave points and an arbitrary point which is on the edge right between the two concave points. A radius set is extracted from all the circles, and a segments set is determined by the edge fragments between all the two adjacent concave points. Based on the radius set and the segments set, we can determine if there is a large gap in the radius set and the length of segments corresponding to the radius. The edge segments and radius set are divided into two subsets, while the appropriate radius range and threshold are selected respectively from the two subsets to execute the Bounded Erosion-Fast Radial Symmetry transform to get the seed point for each object. Our experiments are taken under synthetic and real datasets, in which the overlapping objects in these datasets are with different size. The experimental outcomes show that the proposed approach outperforms other existing schemes.

[1]  Joakim Lindblad,et al.  Robust Cell Image Segmentation Methods , 2004 .

[2]  Hui Kong,et al.  Automated segmentation of abnormal cervical cells using global and local graph cuts , 2014, 2014 IEEE 11th International Symposium on Biomedical Imaging (ISBI).

[3]  Qing Yang,et al.  Iterative Voting for Inference of Structural Saliency and Characterization of Subcellular Events , 2007, IEEE Transactions on Image Processing.

[4]  Nelson H. C. Yung,et al.  Curvature scale space corner detector with adaptive threshold and dynamic region of support , 2004, ICPR 2004.

[5]  Tony F. Chan,et al.  A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model , 2002, International Journal of Computer Vision.

[6]  Mostafa A. El-Sayed,et al.  Shape Transformation and Surface Melting of Cubic and Tetrahedral Platinum Nanocrystals , 1998 .

[7]  Laurent Jacques,et al.  Cell segmentation with random ferns and graph-cuts , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[8]  Carlos S. Pereira,et al.  Detection of Lung Nodule Candidates in Chest Radiographs , 2007, IbPRIA.

[9]  Jitendra Malik,et al.  Normalized Cuts and Image Segmentation , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Rudwan A. Husain,et al.  Image segmentation with improved watershed algorithm using radial bases function neural networks , 2015, 2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA).

[11]  J. Hafner,et al.  Optical properties of star-shaped gold nanoparticles. , 2006, Nano letters.

[12]  Bensheng Qiu,et al.  Active Contour-Based Cell Segmentation During Freezing and Its Application in Cryopreservation , 2015, IEEE Transactions on Biomedical Engineering.

[13]  May D. Wang,et al.  Automated cell counting and cluster segmentation using concavity detection and ellipse fitting techniques , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[14]  J J Vaquero,et al.  Applying watershed algorithms to the segmentation of clustered nuclei. , 1998, Cytometry.

[15]  Oliver Schmitt,et al.  Morphological multiscale decomposition of connected regions with emphasis on cell clusters , 2009, Comput. Vis. Image Underst..

[16]  Sabine Neuss,et al.  Size-dependent cytotoxicity of gold nanoparticles. , 2007, Small.

[17]  Yu Ding,et al.  Segmentation, Inference and Classification of Partially Overlapping Nanoparticles , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[18]  Wenhui Zhang,et al.  A method for recognizing overlapping elliptical bubbles in bubble image , 2012, Pattern Recognit. Lett..

[19]  Heikki Haario,et al.  Segmentation of Overlapping Elliptical Objects in Silhouette Images , 2015, IEEE Transactions on Image Processing.

[20]  Tiexiang Wen,et al.  Segmenting multiple overlapping Nuclei in H&E Stained Breast Cancer Histopathology Images based on an improved watershed , 2015 .

[21]  Alexander Zelinsky,et al.  Fast Radial Symmetry for Detecting Points of Interest , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Heikki Haario,et al.  Segmentation of Partially Overlapping Nanoparticles Using Concave Points , 2015, ISVC.

[23]  Tomasz Markiewicz,et al.  Cell segmentation in desmoglein-3 stained specimen microscopic images using GVF and watershed algorithm , 2016, 2016 17th International Conference Computational Problems of Electrical Engineering (CPEE).