Object Localization Based on Directional Information: Case of 2D Raster Data

Matsakis, Pascal; Ni, Jingbo; Wang, Xin

doi:10.1109/icpr.2006.879

Cited by 8 publications

(8 citation statements)

References 16 publications

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“…We have used it here to determine the behavior of the force histogram towards any invertible affine transformation. In the future, it should help us solve other issues, such as the inverse problem [6], object localization [22] and histogram composition [23]. We will also show that it can be extended to 3-D raster data, like the standard definition [24], and we will examine the case of vector data.…”

Section: Resultsmentioning

confidence: 99%

An equivalent definition of the histogram of forces: Theoretical and algorithmic implications

Matsakis

2010

Pattern Recognition

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Section: Resultsmentioning

confidence: 99%

An equivalent definition of the histogram of forces: Theoretical and algorithmic implications

Matsakis

2010

Pattern Recognition

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“…Two approximation algorithms (one based on a morphological approach [1] and one based on the partitioning of the image into parallel raster lines [11]) have been proposed and are commonly used [8,9,10]. Standard maps, unfortunately, have important flaws, as will be shown in Section 5.…”

Section: Directional Mapsmentioning

confidence: 99%

Directional relationships to a reference object: A quantitative approach based on force fields

Matsakis

Veltman

2009

2009 16th IEEE International Conference on Image Processing (ICIP)

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A directional map (or spatial template, fuzzy landscape) is an image where the value of each pixel represents the degree to which the pixel satisfies some directional relationship (e.g., right, left, above, below) to some reference object (i.e., a given set of pixels). There exists a simple quantitative model of such relationships, and the computation of directional maps is usually based on algorithmic implementations of this model. We show here that the model has important flaws, and we respond to the issue with a new, promising approach: all directional maps induced by the reference object are generated from a force field that the object (which is seen as a physical entity) creates around itself. Preliminary experiments illustrate and show the interest of the approach.

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“…5 to 9 lead to a new approximation algorithm, which is faster and gives better results than the algorithm presented in [6]. Details can be found in [11].…”

Section: F-templatesmentioning

confidence: 99%

“…Besides this update procedure, the algorithm is the same as the algorithm presented in [11] (case of crisp objects). The reader can therefore refer to [11] for details on, e.g., optimization and template initialization (which is actually not F δB ← 0).…”

Section: B Implementationmentioning

confidence: 99%

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Fuzzy Object Localization Based on Directional (and Distance) Information

Wang

Matsakis

2006

2006 IEEE International Conference on Fuzzy Systems

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A directional spatial relationship to a reference object (e.g., "east of the post office") can be represented by a spatial template, i.e., a fuzzy subset of the Euclidean space. For each point of the space, the template indicates to what extent the relationship holds. The objects for which the relationship holds best can then be located. In previous work, we discussed the case of crisp 2D objects in raster form. We introduced a new algorithm for directional spatial template computation, which is faster, gives better results and is more flexible than its competitors. The present paper continues this line of research. The algorithm is extended to handle fuzzy objects and embed distance information. In existing models, only angular deviation is taken into account. Spatial distance, however, also contributes in shaping directional templates.

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Object Localization Based on Directional Information: Case of 2D Raster Data

Abstract: Abstract

Cited by 8 publications

References 16 publications

An equivalent definition of the histogram of forces: Theoretical and algorithmic implications

An equivalent definition of the histogram of forces: Theoretical and algorithmic implications

Directional relationships to a reference object: A quantitative approach based on force fields

Fuzzy Object Localization Based on Directional (and Distance) Information

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