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1.
NeTra: A toolbox for navigating large image databases 总被引:17,自引:0,他引:17
We present here an implementation of NeTra, a prototype image retrieval system that uses color, texture, shape and spatial
location information in segmented image regions to search and retrieve similar regions from the database. A distinguishing
aspect of this system is its incorporation of a robust automated image segmentation algorithm that allows object- or region-based
search. Image segmentation significantly improves the quality of image retrieval when images contain multiple complex objects.
Images are segmented into homogeneous regions at the time of ingest into the database, and image attributes that represent
each of these regions are computed. In addition to image segmentation, other important components of the system include an
efficient color representation, and indexing of color, texture, and shape features for fast search and retrieval. This representation
allows the user to compose interesting queries such as “retrieve all images that contain regions that have the color of object
A, texture of object B, shape of object C, and lie in the upper of the image”, where the individual objects could be regions
belonging to different images. A Java-based web implementation of NeTra is available at http://vivaldi.ece.ucsb.edu/Netra. 相似文献
2.
To improve the discrimination power of color-indexing techniques, we encode a minimal amount of spatial information in the
index. We tesselate each image with five partially overlapping, fuzzy regions. In the index, for each region in an image,
we store its average color and the covariance matrix of the color distribution. A similiarity function of these color features
is used to match query images with images in the database. In addition, we propose two measures to evaluate the performance
of image-indexing techniques. We present experimental results using an image database which contains more than 11,600 color
images. 相似文献
3.
The development of a system supporting querying of image databases by color content tackles a major design choice about properties
of colors which are referenced within user queries. On the one hand, low-level properties directly reflect numerical features
and concepts tied to the machine representation of color information. On the other hand, high-level properties address concepts
such as the perceptual quality of colors and the sensations that they convey. Color-induced sensations include warmth, accordance or contrast, harmony, excitement, depression, anguish, etc. In other words, they refer to the semantics of color usage. In particular, paintings are an example where the message is contained more in the high-level color qualities
and spatial arrangements than in the physical properties of colors. Starting from this observation, Johannes Itten introduced
a formalism to analyze the use of color in art and the effects that this induces on the user's psyche. In this paper, we present
a system which translates the Itten theory into a formal language that expresses the semantics associated with the combination
of chromatic properties of color images. The system exploits a competitive learning technique to segment images into regions
with homogeneous colors. Fuzzy sets are used to represent low-level region properties such as hue, saturation, luminance,
warmth, size and position. A formal language and a set of model-checking rules are implemented to define semantic clauses
and verify the degree of truth by which they hold over an image. 相似文献
4.
Comparing images using joint histograms 总被引:11,自引:0,他引:11
Color histograms are widely used for content-based image retrieval due to their efficiency and robustness. However, a color
histogram only records an image's overall color composition, so images with very different appearances can have similar color
histograms. This problem is especially critical in large image databases, where many images have similar color histograms.
In this paper, we propose an alternative to color histograms called a joint histogram, which incorporates additional information without sacrificing the robustness of color histograms. We create a joint histogram
by selecting a set of local pixel features and constructing a multidimensional histogram. Each entry in a joint histogram
contains the number of pixels in the image that are described by a particular combination of feature values. We describe a
number of different joint histograms, and evaluate their performance for image retrieval on a database with over 210,000 images.
On our benchmarks, joint histograms outperform color histograms by an order of magnitude. 相似文献
5.
Fast image retrieval using color-spatial information 总被引:1,自引:0,他引:1
Beng Chin Ooi Kian-Lee Tan Tat Seng Chua Wynne Hsu 《The VLDB Journal The International Journal on Very Large Data Bases》1998,7(2):115-128
In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate
the retrieval process. The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image. Two clusters from two images are similar if they are of the
same color and overlap in the image space. The number of clusters that can be extracted from an image can be very large, and
it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine
an appropriate value for “optimal' performance. To facilitate efficient retrieval, we also propose a multi-tier indexing
mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors,
while the second layer discriminates clusters of different spatial locality. We conducted an experimental study on an image
database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach, and the efficiency
of the proposed indexing mechanism.
Received August 1, 1997 / Accepted December 9, 1997 相似文献
6.
Analyzing scenery images by monotonic tree 总被引:3,自引:0,他引:3
Content-based image retrieval (CBIR) has been an active research area in the last ten years, and a variety of techniques
have been developed. However, retrieving images on the basis of low-level features has proven unsatisfactory, and new techniques
are needed to support high-level queries. Research efforts are needed to bridge the gap between high-level semantics and low-level
features. In this paper, we present a novel approach to support semantics-based image retrieval. Our approach is based on
the monotonic tree, a derivation of the contour tree for use with discrete data. The structural elements of an image are modeled
as branches (or subtrees) of the monotonic tree. These structural elements are classified and clustered on the basis of such
properties as color, spatial location, harshness and shape. Each cluster corresponds to some semantic feature. This scheme
is applied to the analysis and retrieval of scenery images. Comparisons of experimental results of this approach with conventional
techniques using low-level features demonstrate the effectiveness of our approach. 相似文献
7.
Yihong Gong 《Multimedia Systems》1999,7(6):449-457
In this paper, we propose a novel system that strives to achieve advanced content-based image retrieval using seamless combination
of two complementary approaches: on the one hand, we propose a new color-clustering method to better capture color properties
of the original images; on the other hand, expecting that image regions acquired from the original images inevitably contain
many errors, we make use of the available erroneous, ill-segmented image regions to accomplish the object-region-based image
retrieval. We also propose an effective image-indexing scheme to facilitate fast and efficient image matching and retrieval.
The carefully designed experimental evaluation shows that our proposed image retrieval system surpasses other methods under
comparison in terms of not only quantitative measures, but also image retrieval capabilities. 相似文献
8.
Blobworld: image segmentation using expectation-maximization and its application to image querying 总被引:23,自引:0,他引:23
Carson C. Belongie S. Greenspan H. Malik J. 《IEEE transactions on pattern analysis and machine intelligence》2002,24(8):1026-1038
Retrieving images from large and varied collections using image content as a key is a challenging and important problem. We present a new image representation that provides a transformation from the raw pixel data to a small set of image regions that are coherent in color and texture. This "Blobworld" representation is created by clustering pixels in a joint color-texture-position feature space. The segmentation algorithm is fully automatic and has been run on a collection of 10,000 natural images. We describe a system that uses the Blobworld representation to retrieve images from this collection. An important aspect of the system is that the user is allowed to view the internal representation of the submitted image and the query results. Similar systems do not offer the user this view into the workings of the system; consequently, query results from these systems can be inexplicable, despite the availability of knobs for adjusting the similarity metrics. By finding image regions that roughly correspond to objects, we allow querying at the level of objects rather than global image properties. We present results indicating that querying for images using Blobworld produces higher precision than does querying using color and texture histograms of the entire image in cases where the image contains distinctive objects. 相似文献
9.
Anne H.H. Ngu Quan Z. Sheng Du Q. Huynh Ron Lei 《The VLDB Journal The International Journal on Very Large Data Bases》2001,9(4):279-293
The optimized distance-based access methods currently available for multidimensional indexing in multimedia databases have
been developed based on two major assumptions: a suitable distance function is known a priori and the dimensionality of the
image features is low. It is not trivial to define a distance function that best mimics human visual perception regarding
image similarity measurements. Reducing high-dimensional features in images using the popular principle component analysis
(PCA) might not always be possible due to the non-linear correlations that may be present in the feature vectors. We propose
in this paper a fast and robust hybrid method for non-linear dimensions reduction of composite image features for indexing
in large image database. This method incorporates both the PCA and non-linear neural network techniques to reduce the dimensions
of feature vectors so that an optimized access method can be applied. To incorporate human visual perception into our system,
we also conducted experiments that involved a number of subjects classifying images into different classes for neural network
training. We demonstrate that not only can our neural network system reduce the dimensions of the feature vectors, but that
the reduced dimensional feature vectors can also be mapped to an optimized access method for fast and accurate indexing.
Received 11 June 1998 / Accepted 25 July 2000 Published online: 13 February 2001 相似文献
10.
We propose a system that simultaneously utilizes the stereo disparity and optical flow information of real-time stereo grayscale
multiresolution images for the recognition of objects and gestures in human interactions. For real-time calculation of the
disparity and optical flow information of a stereo image, the system first creates pyramid images using a Gaussian filter.
The system then determines the disparity and optical flow of a low-density image and extracts attention regions in a high-density
image. The three foremost regions are recognized using higher-order local autocorrelation features and linear discriminant
analysis. As the recognition method is view based, the system can process the face and hand recognitions simultaneously in
real time. The recognition features are independent of parallel translations, so the system can use unstable extractions from
stereo depth information. We demonstrate that the system can discriminate the users, monitor the basic movements of the user,
smoothly learn an object presented by users, and can communicate with users by hand signs learned in advance.
Received: 31 January 2000 / Accepted: 1 May 2001
Correspondence to: I. Yoda (e-mail: yoda@ieee.org, Tel.: +81-298-615941, Fax: +81-298-613313) 相似文献