Mathematical Morphology on the Spherical CIELab Quantale with an Application in Color Image Boundary Detection

Mathematical morphology is a theory with applications in image processing and analysis. This paper presents a quantale-based approach to color morphology based on the CIELab color space in spherical coordinates. The novel morphological operations take into account the perceptual difference between color elements by using a distance-based ordering scheme. Furthermore, the novel approach allows for the use of non-flat structuring elements. An illustrative example reveals that non-flat dilations and erosions may preserve more features of a color image than their corresponding flat operations. Furthermore, the novel non-flat morphological operators yielded promising results on experiments concerning the detection of the boundaries of objects on color images.

[1]  Cris L. Luengo Hendriks,et al.  Mathematical Morphology and Its Application to Signal and Image Processing, 9th International Symposium, ISMM 2009, Groningen, The Netherlands, August 24-27, 2009 Proceedings , 2009, ISMM.

[2]  Manuel González Hidalgo,et al.  On the Choice of the Pair Conjunction–Implication Into the Fuzzy Morphological Edge Detector , 2015, IEEE Transactions on Fuzzy Systems.

[3]  Jos B. T. M. Roerdink,et al.  Generalized Morphology using Sponges , 2016, Math. Morphol. Theory Appl..

[4]  Jon Atli Benediktsson,et al.  Mathematical Morphology and Its Applications to Signal and Image Processing , 2015, Lecture Notes in Computer Science.

[5]  John G. Stell,et al.  Why Mathematical Morphology Needs Quantales , 2009 .

[6]  Noël Richard,et al.  Spectral Ordering Assessment Using Spectral Median Filters , 2015, ISMM.

[7]  Moni Naor,et al.  Image Analysis and Recognition , 2016, Lecture Notes in Computer Science.

[8]  Petros Maragos,et al.  Lattice Image Processing: A Unification of Morphological and Fuzzy Algebraic Systems , 2005, Journal of Mathematical Imaging and Vision.

[9]  Jesús Angulo,et al.  The Irregularity Issue of Total Orders on Metric Spaces and Its Consequences for Mathematical Morphology , 2015, Journal of Mathematical Imaging and Vision.

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

[11]  Henk J. A. M. Heijmans,et al.  Grey-Scale Morphology Based on Fuzzy Logic , 2002, Journal of Mathematical Imaging and Vision.

[12]  Rafael Muñoz-Salinas,et al.  A novel method to look for the hysteresis thresholds for the Canny edge detector , 2011, Pattern Recognit..

[13]  Marcos Eduardo Valle,et al.  Elementary Morphological Operations on the Spherical CIELab Quantale , 2015, ISMM.

[14]  Kristel Michielsen,et al.  Morphological image analysis , 2000 .

[15]  Etienne E. Kerre,et al.  A Lattice-Based Approach to Mathematical Morphology for Greyscale and Colour Images , 2007, Computational Intelligence Based on Lattice Theory.

[16]  Bernhard Burgeth,et al.  An approach to color-morphology based on Einstein addition and Loewner order , 2014, Pattern Recognit. Lett..

[17]  Sébastien Lefèvre,et al.  On the morphological processing of hue , 2009, Image Vis. Comput..

[18]  Bernard De Baets,et al.  A Fuzzy Morphology: a Logical Approach , 1998 .

[19]  Etienne E. Kerre,et al.  On the role of complete lattices in mathematical morphology: From tool to uncertainty model , 2011, Inf. Sci..

[20]  Etienne E. Kerre,et al.  Connections between binary, gray-scale and fuzzy mathematical morphologies , 2001, Fuzzy Sets Syst..

[21]  Edward J. Delp,et al.  Morphological operations for color image processing , 1999, J. Electronic Imaging.

[22]  Sébastien Lefèvre,et al.  A hit-or-miss transform for multivariate images , 2009, Pattern Recognit. Lett..

[23]  Ciro Russo Quantale Modules and their Operators, with Applications , 2010, J. Log. Comput..

[24]  Audrey Ledoux,et al.  Toward a Complete Inclusion of the Vector Information in Morphological Computation of Texture Features for Color Images , 2014, ICISP.

[25]  Henk J. A. M. Heijmans,et al.  Mathematical Morphology: A Modern Approach in Image Processing Based on Algebra and Geometry , 1995, SIAM Rev..

[26]  Jean Paul Frédéric Serra,et al.  A Lattice Approach to Image Segmentation , 2005, Journal of Mathematical Imaging and Vision.

[27]  Jean Paul Frédéric Serra,et al.  The "False Colour" Problem , 2009, ISMM.

[28]  Ean,et al.  MATHEMATICAL MORPHOLOGY IN THE CIELAB SPACE A , 2022 .

[29]  Sébastien Lefèvre,et al.  A comparative study on multivariate mathematical morphology , 2007, Pattern Recognit..

[30]  H. Heijmans,et al.  The algebraic basis of mathematical morphology , 1988 .

[31]  Stanley R Sternberg,et al.  Grayscale morphology , 1986 .

[32]  Jesús Angulo,et al.  Morphological colour operators in totally ordered lattices based on distances: Application to image filtering, enhancement and analysis , 2007, Comput. Vis. Image Underst..

[33]  Arthur R. Weeks,et al.  Morphological operations on color images , 2001, J. Electronic Imaging.

[34]  Peter Sussner,et al.  Classification of Fuzzy Mathematical Morphologies Based on Concepts of Inclusion Measure and Duality , 2008, Journal of Mathematical Imaging and Vision.

[35]  Stephen Herman Feature-Size Dependent Selective Edge Enhancement Of X-Ray Images , 1988, Medical Imaging.

[36]  Ulisses Braga-Neto,et al.  Supremal Multiscale Signal Analysis , 2004, SIAM J. Math. Anal..

[37]  Xiaobo Li,et al.  Boundary detection using mathematical morphology , 1995, Pattern Recognit. Lett..

[38]  Jos B. T. M. Roerdink,et al.  Group-Invariant Colour Morphology Based on Frames , 2014, IEEE Transactions on Image Processing.

[39]  Tinku Acharya,et al.  Image Processing: Principles and Applications , 2005, J. Electronic Imaging.

[40]  Sébastien Lefèvre,et al.  On lexicographical ordering in multivariate mathematical morphology , 2008, Pattern Recognit. Lett..

[41]  Allan Hanbury,et al.  Morphological operators on the unit circle , 2001, IEEE Trans. Image Process..

[42]  Peter Sussner,et al.  Quantale-based autoassociative memories with an application to the storage of color images , 2013, Pattern Recognit. Lett..

[43]  Jos B. T. M. Roerdink,et al.  Sponges for Generalized Morphology , 2015, ISMM.

[44]  Isabelle Bloch,et al.  Lattices of fuzzy sets and bipolar fuzzy sets, and mathematical morphology , 2011, Inf. Sci..

[45]  Krishnamoorthy Sivakumar,et al.  Morphological Operators for Image Sequences , 1995, Comput. Vis. Image Underst..

[46]  Pierre Soille,et al.  Morphological Image Analysis: Principles and Applications , 2003 .

[47]  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.

[48]  Roberto de Alencar Lotufo,et al.  Analysis of Scalar Maps for the Segmentation of the Corpus Callosum in Diffusion Tensor Fields , 2012, Journal of Mathematical Imaging and Vision.

[49]  Christian Ronse,et al.  Why mathematical morphology needs complete lattices , 1990, Signal Process..

[50]  Jos B. T. M. Roerdink,et al.  Frames, the Loewner order and eigendecomposition for morphological operators on tensor fields , 2014, Pattern Recognit. Lett..

[51]  Jos B. T. M. Roerdink,et al.  Group-Invariant Frames for Colour Morphology , 2013, ISMM.

[52]  Mihai Ivanovici,et al.  Probabilistic pseudo-morphology for grayscale and color images , 2014, Pattern Recognit..

[53]  Hazem Al-Otum A novel set of image morphological operators using a modified vector distance measure with color pixel classification , 2015, J. Vis. Commun. Image Represent..

[54]  Gerhard X. Ritter,et al.  Computational Intelligence Based on Lattice Theory , 2007, Studies in Computational Intelligence.

[55]  Peter Sussner,et al.  Morphological perceptrons with competitive learning: Lattice-theoretical framework and constructive learning algorithm , 2011, Inf. Sci..

[56]  Olivier Lézoray,et al.  Complete lattice learning for multivariate mathematical morphology , 2016, J. Vis. Commun. Image Represent..

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

[58]  Henk J. A. M. Heijmans,et al.  The algebraic basis of mathematical morphology. I Dilations and erosions , 1990, Comput. Vis. Graph. Image Process..

[59]  Etienne E. Kerre,et al.  Vector Morphological Operators for Colour Images , 2005, ICIAR.

[60]  Hugues Talbot,et al.  Complete ordering and multivariate mathematical morphology , 1998 .

[61]  Noël Richard,et al.  Perceptual color hit-or-miss transform: application to dermatological image processing , 2015, Signal Image Video Process..

[62]  Anke Meyer-Bäse,et al.  Elementary Morphology for SO(2)- and SO(3)-Orientation Fields , 2015, ISMM.