Mohammad NAEEM, Nasir AHMAD, Sahib KHAN, Asma GUL

A fuzzy model of directional relationships from the phi-descriptor

Directional spatial relationships are a category of spatial relationships and have applications in the fields of image processing, geographic information systems, natural language processing, and robot navigation. They can be directly extracted from images or can be interpreted from a type of image descriptors called the relative position descriptors. Examples of relative position descriptors are the angle histogram, the force histogram, and the recently proposed phi-descriptor. So far, fuzzy models of directional spatial relationships from the angle histogram and force histograms have been proposed in the literature. These include the compatibility method, the aggregation method, and the method of effective forces. However, extraction of directional spatial relationships from the phi-descriptor has not been investigated. In this work, the first fuzzy model of directional spatial relationships from the phi-descriptor is presented. The model calculates the truth degree of a directional spatial proposition (e.g. object A is to the right of object B) about two objects from the average angle between the objects. Furthermore, it takes into account the angle which the argument object subtends the reference object when calculating the truth-degree. A novelty of the proposed model is the use of the cone concept in the calculation of the average direction and the handling of boundary cases. The model was tested on standard image data and the results were compared with those of the existing models. The performance is found to be satisfactory and the results meet users' perceptions and expectations.

Keywords:

Directional spatial relationships, topological spatial relationships distance spatial relationships, spatial relationships, relative position descriptors, the phi-descriptor,

PDF

___

Freeman J. The modeling of spatial relations. Comput Vision Graph 1975; 4: 156-171.
Bui AAT, Ricky KT. Organizing observations: data models. In: Bui AAT, Ricky KT, editors. Medical Imaging Informatics. Boston, MA, USA: Springer, 2010. pp. 299-331.
Bloch I. Fuzzy relative position between objects in image processing: a morphological approach. IEEE T Pattern Anal 1999; 21: 657-664.
Matsakis P, Wendling L. A new way to represent a relative position between aerial objects. IEEE T Pattern Anal 1999; 21: 634-642.
Miyajima K, Ralescu A. Spatial organization in 2D segmented images: representation and recognition of primitive spatial relations. Fuzzy Set Syst 1994; 65: 225-236.
Miyajima K, Ralescu A. Spatial organization in 2D images, fuzzy systems. In: IEEE 3rd World Congress on Computational Intelligence; 26–29 June 1994; Orlando, FL, USA: IEEE. pp. 100-105.
Wang Y, Makedon F, Ford J, Shen L, Goldin D. Generating fuzzy semantic metadata describing spatial relations from images using the R-histogram. In: Joint ACM/IEEE Conference on Digital Libraries; 07–11 June 2004; Tucson, AZ, USA: IEEE. pp. 202-2011.
Zhang K, Wang KP, Wang XJ, Zhong YX. Spatial relations modeling based on visual area histogram. In: 11th ACIS Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel Distributed Computing (SNPD); 9–11 June 2010; London, UK: IEEE. pp. 97-101.
Keller JM, Wang X. A comparison of spatial relation definitions in computer vision. In: 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society (ISUMNA-NAFIPS); 17–20 September 1995; College Park, MD, USA: IEEE. pp. 679-684.
Karishnaporum K, Keller JM, Ma Y. Quantitative analysis of properties and spatial relations of fuzzy image regions. IEEE T Fuzzy Syst 1993; 1: 222-233.
Matsakis P, Keller JM. Linguistic description of relative position in images. IEEE T Syst Man CY B 2001; 31: 573-587.
Matsakis P, Naeem M, Rahbania F. Introducing the phi-descriptor: A most versatile relative position descriptor. In: 4th International Conference on Pattern Recognition Applications and Methods; 10–12 January 2015; Lisbon, Portugal: ICPRAM. pp. 87-98.
Keller JM, Matsakis P. Aspects of high-level computer vision using fuzzy sets. In: IEEE International Conference on Fuzzy Systems; 22–25 August 1999; Seoul, Korea: IEEE. pp. 847-852.
Allen JF. Maintaining knowledge about temporal intervals. Commun ACM 1983; 26: 832-843.
Meneghetti C, Pazzaglia F, Beni RD. Spatial mental representations derived from survey and route descriptions: When individuals prefer extrinsic frame of reference. Learn Individ Differ 2011; 21: 150-157.
Retz-Schmidt G. Various views on spatial propositions. AI Mag 1988; 9: 95-105.
Gapp KP. Angle, distance, shape, and their relationship to projective relations. In: Seventeenth Conference of the Cognitive Science Society; 22–25 July 1995; Pittsburgh, PA, USA: pp. 112-117.
Da Silva JA, Karla DF. Addition of the directionality concept in spatial queries on SDMSs using the union of the cone-based and projection-based models. In: 14th Brazilian Symposium on Geoinformatics (GEOINFO); 24–27 November 2013; Campos do Jordão, Brazil: pp. 2179-4820.
Matsakis P, Naeem M. Fuzzy models of topological relationships based on the PHI-descriptor. In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE); 24–29 July 2016; Vancouver, BC, Canada: IEEE. pp. 1096-1104.

Turkish Journal of Electrical Engineering and Computer Science-Cover

ISSN: 1300-0632
Yayın Aralığı: Yılda 6 Sayı
Yayıncı: TÜBİTAK

Arşiv