A Radial Basis Function and Semantic Learning Space Based Composite Learning Approach to Image Retrieval

Shkurko, Konstantin; Qi, Xiaojun

doi:10.1109/icassp.2007.366065

Cited by 9 publications

(3 citation statements)

References 12 publications

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“…For example, in content-based image retrieval systems, the features of an image query are used to search for similar features of images in the database [16,[21][22][23][24].…”

Section: Image Retrieval Approachesmentioning

confidence: 99%

An efficient image retrieval scheme for colour enhancement of embedded and distributed surveillance images

et al. 2016

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a b s t r a c tFrom the past few years, the size of the data grows exponentially with respect to volume, velocity, and dimensionality due to wide spread use of embedded and distributed surveillance cameras for security reasons. In this paper, we have proposed an integrated approach for biometric-based image retrieval and processing which addresses the two issues. The first issue is related to the poor visibility of the images produced by the embedded and distributed surveillance cameras, and the second issue is concerned with the effective image retrieval based on the user query. This paper addresses the first issue by proposing an integrated image enhancement approach based on contrast enhancement and colour balancing methods. The contrast enhancement method is used to improve the contrast, while the colour balancing method helps to achieve a balanced colour. Importantly, in the colour balancing method, a new process for colour cast adjustment is introduced which relies on statistical calculation. It adjusts the colour cast and maintains the luminance of the image. The integrated image enhancement approach is applied to the enhancement of low quality images produced by surveillance cameras. The paper addresses the second issue relating to image retrieval by proposing a content-based image retrieval approach. The approach is based on the three features extraction methods namely colour, texture and shape. Colour histogram is used to extract the colour features of an image. Gabor filter is used to extract the texture features and the moment invariant is used to extract the shape features of an image. The use of these three algorithms ensures that the proposed image retrieval approach produces results which are highly relevant to the content of an image query, by taking into account the three distinct features of the image and the similarity metrics based on Euclidean measure. In order to retrieve the most relevant images, the proposed approach also employs a set of fuzzy heuristics to improve the quality of the results further. The results show the proposed approaches perform better than the well-known existing approaches.

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“…For example, in content-based image retrieval systems, the features of an image query are used to search for similar features of images in the database [16,[21][22][23][24].…”

Section: Image Retrieval Approachesmentioning

confidence: 99%

An efficient image retrieval scheme for colour enhancement of embedded and distributed surveillance images

et al. 2016

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“…These image contents could be extracted from image and could be used for measuring the similarity amid the queried image and images in the database using different statistical methods. In content-based retrieval systems different features of an image query are exploited to search for analogous images features in the database [8]- [10].…”

Section: Content Based Image Retrieval (Cbir) Is a Powerful Toolmentioning

confidence: 99%

Content-Based Image Retrieval Using Texture Color Shape and Region

Shirazi¹,

Umar²,

Naz³

et al. 2016

ijacsa

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Abstract-Interests to accurately retrieve required images from databases of digital images are growing day by day. Images are represented by certain features to facilitate accurate retrieval of the required images. These features include Texture, Color, Shape and Region. It is a hot research area and researchers have developed many techniques to use these feature for accurate retrieval of required images from the databases. In this paper we present a literature survey of the Content Based Image Retrieval (CBIR) techniques based on Texture, Color, Shape and Region. We also review some of the state of the art tools developed for CBIR.

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“…In this thesis, Gaussian radial basis function is considered in McRBFN. However, the Cauchy radial basis function is preferred in applications like image retrieval [149] and computerized tomography [150], while inverse multi-quadratic radial basis function is preferred in real-time signal processing application [151]. A q-Gaussian function parameterizes standard Gaussian distribution by replacing exponential expressions with q-exponential expressions [152].…”

Section: Selection Of Radial Basis Function In Mcrbfnmentioning

confidence: 99%

Meta-cognitive sequential learning in RBF network for diagnosis of neurodegenerative diseases

Babu¹

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Mahanand for their numerous helpful comments and enlightening discussions throughout my research course. Their time and assistance were a valuable contribution to this research work. I would also like to dedicate this special thanks to my family and friends, especially my parents, who have always been there for me. This research work would not have been possible without their love and encouragements. Thanks are also dedicated to Center for Computational Intelligence for the research facilities. I also acknowledge Nanyang Technological University for the nancial support and this precious opportunity of study. Finally, I pay my tributes to the God Almighty

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A Radial Basis Function and Semantic Learning Space Based Composite Learning Approach to Image Retrieval

Cited by 9 publications

References 12 publications

An efficient image retrieval scheme for colour enhancement of embedded and distributed surveillance images

An efficient image retrieval scheme for colour enhancement of embedded and distributed surveillance images

Content-Based Image Retrieval Using Texture Color Shape and Region

Meta-cognitive sequential learning in RBF network for diagnosis of neurodegenerative diseases

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