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Efficient image database retrieval using wavelet packets and Principal Component Analysis

Efficient image database retrieval using wavelet packets and...

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conference on Wavelet Applications in Signal and image Processing Vii

作者： Saeed, M Rabiee, H MIT Dept Elect Engn & Comp Sci Cambridge MA 02139 USA

ISBN: (纸本)0819432997

With the advancement of multimedia technology and the internet, numerous applications have arisen which require the storage and retrieval of large image and video databases. A novel method (Eigenwavelet) was developed to retrieve images from a large heterogeneous image database upon a user-specified query. The queries are in the form of an image(s) that the user seeks to find similar matches to in the database. Using the queries, an efficient algorithm was developed which decomposed each image in the database using wavelet packet analysis. Along each node of the packet tree, Principal Component Analysis (PCA) was applied to the: database images after wavelet packet decomposition, and a set of eigenvectors were generated for each node of the packet tree. To search the image database, the query images are projected onto these eigenvectors (Eigenwavelet coefficients). A distance metric is computed between the projections of the queries and the projections of the images in the database onto the eigenwavelets. Those images with minimal distance (L1) are retrieved in response to a unique query set. Simulations with a heterogeneous image database suggest the Eigenwavelet method of image retrieval is a robust and computationally tractable method of retrieving images with a probability of detection > .8.

关键词： image retrieval wavelet packets Principal Component Analysis image metrics

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An image retrieval Approach to Setup Difficulty Levels in Training Systems for Endomicroscopy Diagnosis

An Image Retrieval Approach to Setup Difficulty Levels in Tr...

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13th International conference on Medical image Computing and Computer-Assisted Intervention (MICCAI)

作者： Andre, Barbara Vercauteren, Tom Buchner, Anna M. Shahid, Muhammad Waseem Wallace, Michael B. Ayache, Nicholas Mauna Kea Technol Paris France INRIA Asclepios Paris France Hosp Univ Penn Philadelphia PA USA Mayo Clin Jacksonville FL USA

ISBN: (纸本)9783642157448

Learning medical image interpretation is an evolutive process that requires modular training systems, from non-expert to expert users. Our study aims at developing such a system for endomicroscopy diagnosis. It uses a difficulty predictor to try and shorten the physician learning curve. As the understanding of video diagnosis is driven by visual similarities, we propose a content-based video retrieval approach to estimate the level of interpretation difficulty. The performance of our retrieval method is compared with several state of the art methods, and its genericity is demonstrated with two different clinical databases, on the Barrett's Esophagus and on colonic polyps. From our retrieval results, we learn a difficulty predictor against a ground truth given by the percentage of false diagnoses among several physicians. Our experiments show that, although our datasets are not large enough to test for statistical significance, there is a noticeable relationship between our retrieval-based difficulty estimation and the difficulty experienced by the physicians.

关键词： Diagnosis

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image retrieval using local characterization

Image retrieval using local characterization

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International conference on image Processing (ICIP-96)

作者： Schmid, C Mohr, R INRIA F-38330 MONTBONNOT MARTINFRANCE

ISBN: (纸本)0780332598

This paper presents a general method to retrieve images from large databases using images as queries. The method is based on local characteristics which are robust to the group of similarity transformations in the image. images can be retrieved even if they are translated, rotated or scaled. Due to the locality of the characterization, images can be retrieved even if only a small part of the image is given as well as in the presence of occlusions. A voting algorithm, following the idea of a Hough transform, and semi-local constraints allow us to develop a new method which is robust to noise, to scene clutter and small perspective deformations. Experiments show an efficient recognition for different types of images. The approach has been validated on an image database containing 1020 images, some of them being very similar by structure, texture or shape.

关键词： Digital image storage

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image indexing by spatial relationships between salient objects

Image indexing by spatial relationships between salient obje...

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2011 Federated conference on Computer Science and Information Systems, FedCSIS 2011

作者： Ganea, Eugen Brezovan, Marius University of Craiova Bd. Decebal 107 Romania

ISBN: (纸本)9781457700415

In this paper, we presented our technique to extract and to use the spatial relationships between two or more salient objects. Using an object oriented hypergraph data structure, the spatial relationships are determined and stored in an object-oriented database. This work aims to unified the phases of processing, indexing and retrieval of images. The proposed model can be applicable to other types of data (video) and to semantic relations hidden in an image. The structure of the database used for image storage allow the construction of the indexes classes hierarchy in order to improve the results of image retrieval. Our method requires more experiments for datasets which come from different areas and for images which contain more salient objects. © 2011 Polish Info Processing Soc.

关键词： Object-oriented databases

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Quantitative comparison of shot boundary detection metrics

Quantitative comparison of shot boundary detection metrics

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Proceedings of the 1999 7th conference of the storage and retrieval for image and video databases Vii

作者： Ford, Ralph M. Pennsylvania State Univ at Erie Erie PA United States

The detection of shot boundaries in video sequences is an important task for generating indexed video databases. This paper provides a comprehensive quantitative comparison of the metrics that have been applied to shot boundary detection. In addition, several standardized statistical tests that have not been applied to this problem, and three new metrics, are considered. A mathematical framework for quantitatively comparing metrics is supplied. Experimental results based on a video database containing 39,000 frames are included.

关键词： image analysis

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Gaussian mixture model for human skin color and its applications in image and video databases

Gaussian mixture model for human skin color and its applicat...

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Proceedings of the 1999 7th conference of the storage and retrieval for image and video databases Vii

作者： Yang, Ming-Hsuan Ahuja, Narendra Univ of Illinois at Urbara-Champaign Urbana IL United States

This paper is concerned with estimating a probability density function of human skin color using a finite Gaussian mixture model whose parameters are estimated through the EM algorithm. Hawkins' statistical test on the normality and homoscedasticity (common covariance matrix) of the estimated Gaussian mixture models is performed and McLachlan's bootstrap method is used to test the number of components in a mixture. Experimental results show that the estimated Gaussian mixture model fits skin images from a large database. Applications of the estimated density function in image and video databases are presented.

关键词： Feature extraction

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An object-relational database infrastructure for interactive multimedia service

An object-relational database infrastructure for interactive...

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conference on Multimedia storage and Archiving Systems ii

作者： Hu, MJ Miao, CY School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore

ISBN: (纸本)0819426628

Modern interactive multimedia services, such as the video-on-demand (VoD), electronic library, and etc. tend to involve large-scale media archives of audio records, video clips, image banks, and text documents. Thus, these services impose many challenges on designing and implementing new generation database systems. In this paper, we first introduce a new multimedia data model, which could accommodate sophisticated media types, as well as complex relationships among different media entities. Thereafter, an object-relational database infrastructure is proposed, to support applications of the data model developed in our project. The infrastructure is designated both as a framework for designing and implementing multimedia databases, and as a reference model to compare and evaluate different database systems. Features of the proposed infrastructure, as well as its implementation into a prototype multimedia database system, are also discussed in the paper.

关键词： multimedia databases object-relational database model multimedia data model and systems

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Digital image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences ii

Digital Image Processing and Visual Communications Technolog...

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Digital image Processing and Visual Communications Technologies in the Earth and Atmospheric Sciences ii

ISBN: (纸本)0819410209

This conference proceedings contains 23 papers. The topics discussed are earth imagery, remote sensing, geographical information systems, multispectral imagery, map databases, image databases, image storage and retrieval, visualization, environmental monitoring, forest monitoring, ocean monitoring, image processing, image analysis, neural network applications, feature extraction, computer vision, vision algorithms, and learning algorithms.

关键词： Remote sensing

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Multi-modal Associative storage and retrieval Using Hopfield Auto-associative Memory Network 28th

Multi-modal Associative Storage and Retrieval Using Hopfield...

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28th International conference on Artificial Neural Networks (ICANN)

作者： Shriwas, Rachna Joshi, Prasun Ladwani, Vandana M. Ramasubramanian, V. Int Inst Informat Technol Bangalore IIITB Bangalore Karnataka India

ISBN: (纸本)9783030304874;9783030304867

Recently we presented text storage and retrieval in an auto-associative memory framework using the Hopfield neural-network. This realized the ideal functionality of Hopfield network as a content-addressable information retrieval system. In this paper, we extend this result to multi-modal patterns, namely, images with text captions and show that the Hopfield network indeed can store and retrieve such multimodal patterns even in an auto-associative setting. Within this framework, we examine two central issues such as (i) performance characterization to show that the O(N) capacity of the Hopfield network for a network of size N neurons under the Pseudo-inverse learning rule is still retained in the multi-modal case, and (ii) the retrieval dynamics of the multi-modal pattern (i.e., image and caption together) under various types of queries such as image+caption, image only and caption only, in line with a typical multi-modal retrieval system where the entire multi-modal pattern is expected to be retrieved even with a partial query pattern from any of the modalities. We present results related to these two issues on a large database of 7000+ captioned-images and establish the practical scalability of both the storage capacity and the retrieval robustness of the Hopfield network for content-addressable retrieval of multi-modal patterns. We point to the potential of this work to extend to a more wider definition of multi-modality as in multi-media content, with various modalities such as video (image sequence) synchronized with sub-title text, speech, music and non-speech.

关键词： Hopfield network Auto-associative memory Multi-modal storage Multi-modal retrieval Captioned images Content-addressable retrieval

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Scene change detection and feature extraction for MPEG-4 sequences

Scene change detection and feature extraction for MPEG-4 seq...

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7th storage and retrieval for image and video databases conference

作者： Divakaran, A Ito, H Sun, HF Poon, T Mitsubishi Elect Informat Technol Amer Adv Televis Lab New Providence NJ 07974 USA

ISBN: (纸本)0819431273

In this paper we present a new computationally efficient and effective technique for detection of abrupt scene changes in MPEG-4/2 compressed video sequences. We combine the de image based approach of Yeo and Liu(1) with the bit allocation change based approach of Feng, Lo and Mehrpour.(2) The bit allocation based approach has the advantage of computational simplicity since it only requires entropy decoding of the sequence. Since extraction of de images from I-Frames/Objects is simple, the de image based technique of Yeo is a good alternative for comparison of I-frames/objects. For P-frames/objects however, Yeo's algorithm requires additional computation. We find that the bit allocation change based approach is prone to false detection in comparison of intra-coded objects in MPEG-4 sequences. However, if a suspected scene/object change has been located accurately in a group of consecutive frames/objects, the bit allocation based technique quickly and accurately locates the cut point therein. This motivates us to use de image based detection between successive I-Frames/Objects to identify the sub-sequences with scene/object changes, and then use bit allocation based detection to find the cut point therein. Our technique thus has only a marginally greater complexity than the completely bit allocation based technique but has greater accuracy. It is applicable to both MPEG-2 sequences and MPEG-4 multiple-object sequences. In the MPEG-4 multiple object case, we use a weighted sum of the change in each object of the frame using the area of the object as the weight.

关键词： compressed-domain video processing video segmentation MPEG-4 MPEG-2 scene change detection

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