Color Image Retrieval using Fuzzy Similarity Measures and Fuzzy Partitions

Nachtegael, Mike; Weken, Dietrich Van der; Witte, Valérie De; Schulte, Stefan; Mélange, Tom; Kerre, Etienne

doi:10.1109/icip.2007.4379511

Cited by 16 publications

(12 citation statements)

References 16 publications

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“…In those cases where there is nearly no color present in the image we will use the intensity component to identify the dominant "color". For Hue and Value components fuzzy partition [8] was used to model the components which are shown in figure 4(hue component) and figure 5(value/intensity component).…”

Section: ) Algorithm For Proposed Schemementioning

confidence: 99%

“…A fuzzy set A [15] in a universe X is characterized by a X -[0, 1] mapping X A , which associates with every element x in X a degree of membership X A (x) of x in the fuzzy set A [8]. A trapezoidal fuzzy number A [8,16] is a fuzzy set with a trapezoidal-shaped membership function.…”

Section: ) Algorithm For Proposed Schemementioning

confidence: 99%

“…on computer screens. However, for color image retrieval purposes it is more convenient to use a color model that characterizes color with one dimension instead of three [8]. Therefore, the HSI color space is preferred.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Content Based Image Retrieval Systems Using Wavelet and Curvelet Transform

Das¹,

Garg²,

Sahoo³

2012

IJMA

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The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. This paper implements a CBIR system using different feature of images through four different methods, two were based on analysis of color feature and other two were based on analysis of combined color and texture feature using wavelet coefficients of an image. To extract color feature from an image, one of the standard ways i.e. color histogram was used in YCbCr color space and HSV color space. Daubechies' wavelet transformation and Symtel's wavelet transform were performed to extract the texture feature of an image. In this paper a color image retrieval system is illustrated, in which the novelty lies in the use of a fuzzy partition of the HSV color space and wavelet transformation of the fuzzified new image. To increase efficiency of the system finally an image retrieval method was proposed using curvelet transform of an image, which provides an opportunity to extract more accurate texture feature for image retrieval. After obtaining all experimental results, a comparative study was done. From the result it was inferred that curvelet based method gave a better performance as compared to other methods.

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Section: ) Algorithm For Proposed Schemementioning

confidence: 99%

Section: ) Algorithm For Proposed Schemementioning

confidence: 99%

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Comparison of Content Based Image Retrieval Systems Using Wavelet and Curvelet Transform

Das¹,

Garg²,

Sahoo³

2012

IJMA

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“…The underlying logic of fuzzy set theory is commonly referred to as fuzzy logic. Since their introduction, fuzzy set theory and fuzzy logic have given rise to many real-world applications, also in the field of image processing [4], [9].…”

Section: Appendix: Basic Notions From Fuzzy Set Theorymentioning

confidence: 99%

OWA filters: A robust filtering method and its application to color images

Basu

Nachtegael

2009

2009 IEEE Symposium on Computational Intelligence for Image Processing

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Bilateral filtering provides a scheme for noniterative edge-preserving smoothing, but the results could be strongly affected by the presence of outliers. In this paper we develop a robust bilateral filter for color images, and in order to achieve this we propose to improve the bilateral filtering technique [13] by using Ordered Weighted Averaging operators. We adopt a fuzzy logic based approach: if the filtering is considered as a weighted averaging, then each filter is associated with a fuzzy set and the membership values of these fuzzy sets represent the weights. In this context, the bilateral filter is a conjunction of two fuzzy sets in the case of grayscale images: one in the spatial domain and one in a photometric domain. Applied to color images, we propose to extend the conjunction to three fuzzy sets: one in the spatial domain, one in the brightness domain and one in the chromatic domain. Taking into account the robustness of rank filters, we propose to define an OWA filter in order to obtain robust adaptive filters in brightness and chromaticity. The robustness and performance of the filter is illustrated with several experiments, revealing its ability to remove different types of noise in the presence of outliers, while preserving edges. The noise types considered are impulse noise and a combination of Gaussian noise with "salt and pepper" noise types.

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“…the text surrounding the image on a web page) and visual features, and sometimes even focus exclusively on visual features [50,95]. Fuzzy set-based approaches have been successfully applied to measure the similarity of visual features [12,19,49,68]. Due to the use of richer semantics in object-based retrieval, often new types of opportunities arise for the application of fuzzy set theory.…”

Section: Domain-specific Retrievalmentioning

confidence: 99%

Fuzzy Methods on the Web: A Critical Discussion

Schockaert

Makarytska

Cock

2010

35 Years of Fuzzy Set Theory

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Gradual concepts abound in many web-related domains, ranging from the notion of relevance in information retrieval, to the strength of connection in online social networks. As a result, fuzzy set theory is often a natural choice in implementing web systems. In this chapter, we give an overview of applications of fuzzy set theory in this area, focusing in particular on information retrieval, the semantic web, and recommender systems. In each case, we contrast fuzzy methods with other approaches, analyzing why and how the ideas of fuzzy set theory may be beneficial.

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Color Image Retrieval using Fuzzy Similarity Measures and Fuzzy Partitions

Cited by 16 publications

References 16 publications

Comparison of Content Based Image Retrieval Systems Using Wavelet and Curvelet Transform

Comparison of Content Based Image Retrieval Systems Using Wavelet and Curvelet Transform

OWA filters: A robust filtering method and its application to color images

Fuzzy Methods on the Web: A Critical Discussion

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