A New Bayesian Edge-Linking Algorithm Using Single-Target Tracking Techniques

This paper proposes novel edge-linking algorithms capable of producing a set of edge segments from a binary edge map generated by a conventional edge-detection algorithm. These proposed algorithms transform the conventional edge-linking problem into a single-target tracking problem, which is a well-known problem in object tracking. The conversion of the problem enables us to apply sophisticated Bayesian inference to connect the edge points. We test our proposed approaches on real images that are corrupted with noise.

[1]  Adam Herout,et al.  Real-Time Detection of Lines and Grids , 2012, SpringerBriefs in Computer Science.

[2]  Francesc Serratosa,et al.  An interactive method for the image alignment problem based on partially supervised correspondence , 2015, Expert Syst. Appl..

[3]  L. Held,et al.  Gaussian Markov Random Fields: Theory And Applications (Monographs on Statistics and Applied Probability) , 2005 .

[4]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[5]  Joseph J. Lim,et al.  Sketch Tokens: A Learned Mid-level Representation for Contour and Object Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[6]  Cuneyt Akinlar,et al.  PEL: A Predictive Edge Linking algorithm , 2016, J. Vis. Commun. Image Represent..

[7]  Gregory W. Cook,et al.  Multiresolution sequential edge linking , 1995, Proceedings., International Conference on Image Processing.

[8]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[9]  Andrea Cavallaro,et al.  Target Detection and Tracking With Heterogeneous Sensors , 2008, IEEE Journal of Selected Topics in Signal Processing.

[10]  Michael Isard,et al.  A mixed-state condensation tracker with automatic model-switching , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[11]  Michael Isard,et al.  A Smoothing Filter for CONDENSATION , 1998, ECCV.

[12]  Jean-Michel Morel,et al.  A Nonlocal Bayesian Image Denoising Algorithm , 2013, SIAM J. Imaging Sci..

[13]  A. Jevtić,et al.  Ant based edge linking algorithm , 2009, 2009 35th Annual Conference of IEEE Industrial Electronics.

[14]  Michael Isard,et al.  Contour Tracking by Stochastic Propagation of Conditional Density , 1996, ECCV.

[15]  Aly A. Farag,et al.  Edge linking by sequential search , 1995, Pattern Recognit..

[16]  Xuelong Li,et al.  Nonrigid Structure-From-Motion From 2-D Images Using Markov Chain Monte Carlo , 2012, IEEE Transactions on Multimedia.

[17]  Daniel Cremers,et al.  Image segmentation with one shape prior - A template-based formulation , 2012, Image Vis. Comput..

[18]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[19]  Hong Zhang,et al.  Edge linking using geodesic distance and neighborhood information , 2008, 2008 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.

[20]  Gilles Celeux,et al.  EM-based image segmentation using Potts models with external field , 2001 .

[21]  Sanjoy K. Mitter,et al.  A hierarchical approach to high resolution edge contour reconstruction , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[22]  Peter J. W. Rayner,et al.  Unsupervised image segmentation using Markov random field models , 1997, Pattern Recognit..

[23]  Jitendra Malik,et al.  A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

[24]  Nikos Komodakis,et al.  Interactive image segmentation based on synthetic graph coordinates , 2013, Pattern Recognit..

[25]  Siqi Chen,et al.  Level set segmentation with both shape and intensity priors , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[26]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[27]  Xuelong Li,et al.  Robust Visual Tracking Using Structurally Random Projection and Weighted Least Squares , 2015, IEEE Transactions on Circuits and Systems for Video Technology.

[28]  William J. Christmas,et al.  Structural Matching in Computer Vision Using Probabilistic Relaxation , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  Ali Mohammad-Djafari,et al.  Unsupervised Bayesian wavelet domain segmentation using Potts-Markov random field modeling , 2005, J. Electronic Imaging.

[30]  John W. Fisher,et al.  Efficient MCMC sampling with implicit shape representations , 2011, CVPR 2011.

[31]  Jianjiang Feng,et al.  Robust and Efficient Algorithms for Separating Latent Overlapped Fingerprints , 2012, IEEE Transactions on Information Forensics and Security.

[32]  Andrew Blake,et al.  Geodesic star convexity for interactive image segmentation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[33]  S. Shankar Sastry,et al.  Markov Chain Monte Carlo Data Association for Multi-Target Tracking , 2009, IEEE Transactions on Automatic Control.

[34]  Adam Herout,et al.  Review of Hough Transform for Line Detection , 2013 .

[35]  Olga Veksler,et al.  Star Shape Prior for Graph-Cut Image Segmentation , 2008, ECCV.

[36]  John W. Fisher,et al.  MCMC Curve Sampling for Image Segmentation , 2007, MICCAI.

[37]  David H. Marimont,et al.  A probabilistic framework for edge detection and scale selection , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[38]  Ji Won Yoon,et al.  Statistical denoising scheme for single molecule fluorescence microscopic images , 2014, Biomed. Signal Process. Control..

[39]  Longin Jan Latecki,et al.  Contour-based object detection as dominant set computation , 2012, Pattern Recognit..

[40]  Majid Mirmehdi,et al.  Segmentation of Color Textures , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[41]  Pierre Machart.  Morphological Segmentation , 2009 .

[42]  Josef Kittler,et al.  Edge-Labeling Using Dictionary-Based Relaxation , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[43]  Håvard Rue,et al.  Bayesian object recognition with baddeley's delta loss , 1998, Advances in Applied Probability.

[44]  Paul F. Whelan,et al.  Computational approach for edge linking , 2002, J. Electronic Imaging.

[45]  Frank Y. Shih,et al.  Adaptive mathematical morphology for edge linking , 2004, Inf. Sci..