Publication 1999 Issue No. 7 - July Abstract - Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach
Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach
July 1999 (vol. 21 no. 7)
pp. 657-664
 ASCII Text x Isabelle Bloch, "Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 7, pp. 657-664, July, 1999.
 BibTex x @article{ 10.1109/34.777378,author = {Isabelle Bloch},title = {Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach},journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},volume = {21},number = {7},issn = {0162-8828},year = {1999},pages = {657-664},doi = {http://doi.ieeecomputersociety.org/10.1109/34.777378},publisher = {IEEE Computer Society},address = {Los Alamitos, CA, USA},}
 RefWorks Procite/RefMan/Endnote x TY - JOURJO - IEEE Transactions on Pattern Analysis and Machine IntelligenceTI - Fuzzy Relative Position Between Objects in Image Processing: A Morphological ApproachIS - 7SN - 0162-8828SP657EP664EPD - 657-664A1 - Isabelle Bloch, PY - 1999KW - Fuzzy setsKW - spatial relative positionKW - directional relationsKW - fuzzy mathematical morphologyKW - structural shape recognition.VL - 21JA - IEEE Transactions on Pattern Analysis and Machine IntelligenceER -

Abstract—In order to cope with the ambiguity of spatial relative position concepts, we propose a new definition of the relative position between two objects in a fuzzy set framework. This definition is based on a morphological and fuzzy pattern-matching approach, and consists of comparing an object to a fuzzy landscape representing the degree of satisfaction of a directional relationship to a reference object. It has good formal properties, it is flexible, it fits the intuition, and it can be used for structural pattern recognition under imprecision. Moreover, it also applies in 3D and for fuzzy objects issued from images.

[1] I. Block, “Fuzzy Relative Position Between Objects in Images: A Morphological Approach,” Proc. Int'l Conf. Image Processing Proc., 96, vol. II, pp. 987-990, Lausanne, Switzerland, 1996.
[2] I. Bloch, "Fuzzy Spatial Relationships: A Few Tools for Model-Based Pattern Recognition in Aerial Images," Proc. SPIE/EUROPTO Conf. Image and Signal Processing for Remote Sensing, vol. 2,955, pp. 141-152,Taormina, Italy, Sept. 1996.
[3] I. Bloch, "Image Information Processing Using Fuzzy Sets," Proc. World Automation Congress, Soft Computing with Industrial Applications, invited conference, pp. 79-84,Montpellier, France, May 1996.
[4] I. Bloch, "Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach," Technical Report No. 97D003, ENST, Paris, 1997.
[5] I. Bloch and H. ${\rm Ma\hat itre}$, "Fuzzy Mathematical Morphologies: A Comparative Study," Pattern Recognition, vol. 28, no. 9, pp. 1,341-1,387, 1995.
[6] G. Borgefors, "Distance Transforms in the Square Grid," H.${\rm Ma\hat itre},$ed., Progress in Picture Processing, Les Houches, Session LVIII, 1992, ch. 1.4, pp. 46-80, North-Holland, Amsterdam, 1996.
[7] D. Dubois and H. Prade, "A Review of Fuzzy Set Aggregation Connectives," Information Sciences, vol. 36, pp. 85-121, 1985.
[8] D. Dubois, H. Prade, and C. Testemale, "Weighted Fuzzy Pattern Matching," Fuzzy Sets and Systems, vol. 28, pp. 313-331, 1988.
[9] S. Dutta, “Approximate Spatial Reasoning: Integrating Qualitative and Quantitative Constraints,” Int'l J. Approximate Reasoning, vol. 5, pp. 307-331, 1991.
[10] J.M. Keller and X. Wang, “Comparison of Spatial Relation Definitions in Computer Vision,” ISUMA-NAFIPS'95: Special Session on Fuzzy Sets and Systems in Signal Processing Applications, pp. 679-684, Univ. of Maryland, College Park, 1995.
[11] L.T. Kòczy, “On the Description of Relative Position of Fuzzy Patterns,” Pattern Recognition Letters, vol. 8, pp. 21-28, 1988.
[12] R. Krishnapuram and J.M. Keller, "Fuzzy Set Theoretic Approach to Computer Vision: An Overview," Proc. IEEE Int'l Conf. Fuzzy Systems, pp. 135-142,San Diego, 1992.
[13] R. Krishnapuram, J.M. Keller, and Y. Ma, “Quantitative Analysis of Properties and Spatial Relations of Fuzzy Image Regions,” IEEE Trans. Fuzzy Systems, vol. 1, no. 3, pp. 222-233, 1993.
[14] P. Matsakis and L. Wendling, A New Way to Represent Relative Position between Areal Objects IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 7, pp. 634-643, July 1999.
[15] K. Miyajima and A. Ralescu, “Spatial Organization in 2D Segmented Images: Representation and Recognition of Primitive Spatial Relations” Fuzzy Sets and Systems, vol. 65, pp. 225-236, 1994.

Index Terms:
Fuzzy sets, spatial relative position, directional relations, fuzzy mathematical morphology, structural shape recognition.
Citation:
Isabelle Bloch, "Fuzzy Relative Position Between Objects in Image Processing: A Morphological Approach," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 7, pp. 657-664, July 1999, doi:10.1109/34.777378