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Image Retrieval (image + retrieval)

Distribution by Scientific Domains

Information Science and Computing	42%

Selected Abstracts

Does compression affect image retrieval performance?

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 2-3 2008
Gerald Schaefer
Abstract Image retrieval and image compression are both fields of intensive research. As lossy image compression degrades the visual quality of images and hence changes the actual pixel values of an image, low level image retrieval descriptors which are based on statistical properties of pixel values will change, too. In this article we investigate how image compression affects the performance of low-level colour descriptors. Several image retrieval algorithms are evaluated on a speciated image database compressed at different image quality levels. Extensive experiments reveal that while distribution-based colour descriptors are fairly stable with respect to image compression a drop in retrieval performance can nevertheless be observed for JPEG compressed images. On the other hand, after application of JPEG2000 compression only a negligible performance drop is observed even at high compression ratios. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 18, 101,112, 2008 [source]

Parallel heterogeneous CBIR system for efficient hyperspectral image retrieval using spectral mixture analysis

CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 9 2010
Antonio J. Plaza
Abstract The purpose of content-based image retrieval (CBIR) is to retrieve, from real data stored in a database, information that is relevant to a query. In remote sensing applications, the wealth of spectral information provided by latest-generation (hyperspectral) instruments has quickly introduced the need for parallel CBIR systems able to effectively retrieve features of interest from ever-growing data archives. To address this need, this paper develops a new parallel CBIR system that has been specifically designed to be run on heterogeneous networks of computers (HNOCs). These platforms have soon become a standard computing architecture in remote sensing missions due to the distributed nature of data repositories. The proposed heterogeneous system first extracts an image feature vector able to characterize image content with sub-pixel precision using spectral mixture analysis concepts, and then uses the obtained feature as a search reference. The system is validated using a complex hyperspectral image database, and implemented on several networks of workstations and a Beowulf cluster at NASA's Goddard Space Flight Center. Our experimental results indicate that the proposed parallel system can efficiently retrieve hyperspectral images from complex image databases by efficiently adapting to the underlying parallel platform on which it is run, regardless of the heterogeneity in the compute nodes and communication links that form such parallel platform. Copyright © 2009 John Wiley & Sons, Ltd. [source]

An efficient approach to texture-based image retrieval

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 5 2007
Mahmoud R. Hejazi
Abstract In this article, we present an efficient approach for image retrieval based on the textural information of an image, such as orientation, directionality, and regularity. For this purpose, we apply the nonlinear modified discrete Radon transform to estimate these visual contents. We then utilize texture orientation to construct the rotated Gabor transform for extraction of the rotation-invariant texture feature. The rotation-invariant texture feature, directionality, and regularity are the main features used in the proposed approach for similarity assessment. Experimental results on a large number of texture and aerial images from standard databases show that the proposed schemes for feature extraction and image retrieval significantly outperform previous works, including methods based on the MPEG-7 texture descriptors. © 2008 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 295,302, 2007 [source]

Fast gradual matching measure for image retrieval based on visual similarity and spatial relations

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 7 2006
Jean-François Omhover
In this article, we propose a new method to retrieve images containing a request set of regions. The user is asked to specify a set of regions belonging to a single image. Then this request set of regions is compared to the sets of the regions of the images in the database. We propose a comparison measure that not only evaluates the similarity of regions one to the other, but that also takes into account the spatial configuration of the regions. The spatial structure of the regions is represented by means of fuzzy spatial relations, like horizontal and vertical disposal and connexity. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 711,723, 2006. [source]

Exploiting statistical properties of wavelet coefficient for face detection and recognition

PROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2007
Naseer Al-Jawad
Wavelet transforms (WT) are widely accepted as an essential tool for image processing and analysis. Image and video compression, image watermarking, content-base image retrieval, face recognition, texture analysis, and image feature extraction are all but few examples. It provides an alternative tool for short time analysis of quasi-stationary signals, such as speech and image signals, in contrast to the traditional short-time Fourier transform. The Discrete Wavelet Transform (DWT) is a special case of the WT, which provides a compact representation of a signal in the time and frequency domain. In particular, wavelet transforms are capable of representing smooth patterns as well anomalies (e.g. edges and sharp corners) in images. We are focusing here on using wavelet transforms statistical properties for facial feature detection, which allows us to extract the image facial feature/edges easily. Wavelet sub-bands segmentation method been developed and used to clean up the non-significant wavelet coefficients in wavelet sub-band (k) based on the (k-1) sub-band. Moreover, erosion which is considered as one of the fundamental operation in morphological image processing, been used to reduce the unwanted edges in certain directions. For face detection, face template profiles been built for both the face and the eyes for different wavelet sub-band levels to achieve better computational performance, these profiles used to match the extracted profiles from the wavelet domain of the input image using the Dynamic Time Warping technique DTW. The DTW smallest distance allows identifying the face and the eyes location. The performance of face features distances and ratio has been also tested for face verification purposes. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]