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12th IEEE International Symposium on Signal, image, video, and Communications, ISIvC 2024

作者： Daali, Noussaiba Amghar, Souad Mouline, Salma Cherdal, Safae Mohammed V University in Rabat Lrit Faculty of Sciences in Rabat Morocco

ISBN: (纸本)9798350385267

In rapidly evolving data-driven environments, the integration of heterogeneous data sources remains crucial. However, this heterogeneity, inherent in NoSQL databases, presents a significant challenge due to the diversities of the data storage and retrieval methods. This paper presents an automated database schema transformation process into the unified notation proposed in [1] where we gave a NoSQL databases schema integration approach. The three NoSQL schemas considered in this paper are Cassandra, MongoDB, and Couchbase. We use the Model-Driven Engineering (MDE) techniques and the ATL language for each specific database. A case study focused on COvID-19 is used to validate our transformations. © 2024 IEEE.

关键词： Big data

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A generalized prime-number-based matrix strategy for efficient iconic indexing of symbolic pictures

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PATTERN RECOGNITION LETTERS 2001年第6-7期22卷 657-666页

作者： Chang, YI Yang, BY Yeh, WH Natl Sun Yat Sen Univ Dept Comp Sci & Engn Kaohsiung 804 Taiwan Natl Sun Yat Sen Univ Dept Appl Math Kaohsiung 80424 Taiwan

In this paper. we propose an efficient iconic indexing strategy called generalized prime-number-based matrix (GPN Matrix) for symbolic pictures, in which each spatial relationship between any two objects is represented as a product of some prime numbers from a set of 12 prime numbers and is recorded in a matrix. In the proposed strategy, we classify 169 spatial relationships between two objects in 2D space into five spatial categories, and define a generalized category rule (based on module operations) for each of those five spatial categories. As compared to the prime-number-based matrix (PN Matrix) strategy (Chang and Yang, 1997), in which each spatial relationship between any two objects is represented as a product of some prime numbers from a set of 17 prime numbers, the GPN Matrix strategy has a smaller storage space requirement than the PN Matrix strategy. which also improves the query processing time. (C) 2001 Elsevier Science B.v. All rights reserved.

关键词： 2D string 2D C-string image databases pictorial query pictorial databases similarity retrieval spatial reasoning

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Audio as a support to scene change detection and characterization of video sequences

Audio as a support to scene change detection and characteriz...

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1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 97)

作者： Saraceno, C Leonardi, R Univ of Brescia Brescia Italy

ISBN: (纸本)0818679204

A challenging problem to construct video databases is the organization of video information. The development of algorithms able to organize video information according to semantic content of the data is getting more and more important. This will allow algorithms such as indexing and retrieval to work more efficiently. Until now, an attempt to extract semantic information has been performed using only video information. As a video sequence is constructed from a 2-D projection of a 3-D scene, video processing has shown its limitations especially in solving problems such as object identification or object tracking, reducing the ability to extract semantic characteristics. A possibility to overcome the problem is to use additional information. The associated audio signal is then the most natural way to obtain this information. This paper will present a technique which combines video and audio information together for classification and indexing purposes. The classification will be performed on the audio signal;a general framework that uses the results of such classification will then be proposed for organizing video information.

关键词： image segmentation

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A successively refinable wavelet-based representation for content-based image retrieval 1

A successively refinable wavelet-based representation for co...

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IEEE 1st Workshop on Multimedia Signal Processing

作者： Servetto, S Ramchandran, K Huang, TS Coordinated Science Lab Beckman Institute University of Illinois Urbana-Champaign United States

ISBN: (纸本)0780337808

Content based retrieval of image and video data from databases is a very challenging problem, whose interest is derived from the need of future databases to support efficient access to vast amounts of visual information. Typical queries to be performed in this context check attributes of objects present in image data, such as shape, color, relative locations, etc. Therefore, the way in which image data is represented plays a fundamental role in the efficient implementation of those queries. One possibility is to take the naive approach of storing images using standard compression techniques, storing image features (such as object shape descriptors, color histograms, etc.) as explicit side information, and whenever an image is involved in the evaluation of a query decoding it to full resolution;however, much more efficient techniques (in terms of storage and computational requirements) are possible. In this paper, we propose a new image coding technique which combines a wavelet image representation, embedded coding of the wavelet coefficients, and segmentation of semantically meaningful objects in the wavelet domain, to generate a bitstream in which each object is encoded independently of every other object in the image, and without explicitly storing shape boundary information. Furthermore, since the representation of each object is fully embedded applications may, independently for each object, specify the desired target bitrate and retrieve bits from the compressed bitstream. Preliminary results show that our new proposed method achieves PSNR numbers within 0.3dB of those achieved using the same coder without including segmentation information (which is one of the best within its class), thus showing that no severe performance loss results from enabling independent access to objects in the compressed domain.

关键词： image coding

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Audio characterization for video indexing

Audio characterization for video indexing

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storage and retrieval for Still image and video databases Iv

作者： Patel, Nilesh v. Sethi, Ishwar K. Wayne State Univ. Detroit MI USA

ISBN: (纸本)0819420441

The major problem facing video databases is that of content characterization of video clips once the cut boundaries have been determined. The current efforts in this direction are focussed exclusively on the use of pictorial information, thereby neglecting an important supplementary source of content information, i.e. the embedded audio or sound track. The current research in audio processing can be readily applied to create many different video indices for use in video On Demand (vOD), educational video indexing, sports video characterization, etc. MPEG is an emerging video and audio compression standard with rapidly increasing popularity in multimedia industry. Compressed bit stream processing has gained good recognition among the researchers. We have also demonstrated feature extraction in MPEG compressed video which implements a majority of scene change detection schemes on compressed video. In this paper, we examine the potential of audio information for content characterization by demonstrating the extraction of widely used features in audio processing directly from compressed data stream and their application to video clip classification.

关键词： Indexing (of information)

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Data Ingestions as a Service (DIaaS): A Unified Interface for Heterogeneous Data Ingestion, Transformation, and Metadata Management for Data Lake

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IEEE ACCESS 2024年 12卷 156131-156145页

作者： Sreepathy, H. v. Rao, B. Dinesh Jaysubramanian, Mohan Kumar Rao, B. Deepak Manipal Acad Higher Educ Manipal Sch Informat Sci Manipal 576104 India MulticoreWare Frameworks & Tools Coimbatore 641049 India

Data ingestion tools are critical component of Data Lake. Existing data ingestion tools face challenges of handling large variety, formats, sources of data. There exists void for unified data ingestion interface to handle the above research problems. This study proposes an innovative and integrated framework for data ingestion in a data lake, addressing the challenges posed by heterogeneous data sources, formats, and metadata management. The framework comprises three novel modules: First Unified Data Integration Connectors (UDIC), which provide seamless connectivity and data retrieval capabilities from diverse sources including databases, data warehouses, file systems, cloud storage, and APIs;Second, Adaptive Data variety Transformation (ADvT), a module that intelligently handles the transformation and processing of structured, semi-structured, and unstructured data types, ensuring efficient ingestion into the data lake;and third, Intelligent Metadata Management (IMM), a module that captures, stores, and manages metadata associated with the ingested data, offering advanced search, discovery, and enrichment functionalities. Comparative study corroborates features offered by the service with existing data ingestion tools to evaluate the novelty and significance of the study. Performance validation shows varying ingestion latencies across different data types: approximately 148.1 microseconds per record for structured data, 234.2 microseconds per record for semi-structured data, 65.6 microseconds per kilobyte (KB) for video data, and 42.7 microseconds per KB for image data. These results underscore the importance of considering data structure and size in optimizing ingestion processes. Overall, this research aims to revolutionize data ingestion in data lake environments by providing a unified solution for handling diverse data sources, formats, and metadata management.

关键词： Big Data applications Metadata Soft sensors Real-time systems Organizations Java Internet of Things Relational databases File systems Data lakes Data ingestion data lake data sources data formats unified interface data ingestion service big data

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Multiresolution subimage similarity matching for large image databases

Multiresolution subimage similarity matching for large image...

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storage and retrieval for image and video databases vI

作者： Leung, Kai-Sang Ng, Raymond Department of Computer Science The Univ. of British Columbia 2366 Main Mall Vancouver BC V6T 1Z4 Canada

Many database management systems support whole-image matching. However, users may only remember certain subregions of the images. In this paper, we develop Padding and Reduction Algorithms to support subimage queries of arbitrary size based on local color information. The idea is to estimate the best-case lower bound to the dissimilarity measure between the query and the image. By making use of multiresolution representation, this lower bound becomes tighter as the scale becomes finer. Because image contents are usually pre-extracted and stored, a key issue is how to determine the number of levels used in the representation. We address this issue analytically by estimating the CPU and I/O costs, and experimentally by comparing the performance and accuracy of the outcomes of various filtering schemes. Our findings suggest that a 3-level hierarchy is preferred. We also study three strategies for searching multiple resolutions. Our studies indicate that the hybrid strategy with horizontal filtering on the coarse level and vertical filtering on remaining is the best choice when using Padding and Reduction Algorithms in the preferred 3-level multiresolution representation. The best 10 desired images can be retrieved efficiency and effectively from a collection of a thousand images in about 3.5 seconds.

关键词： Content based retrieval

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Advances in visual Information Systems 1

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丛书名： Lecture Notes in Computer Science

1000年

ISBN: (数字)9783540764144

ISBN: (纸本)9783540764137

The visual Information Systems International Conference series is designed to provide a forum for researchers and practitioners from diverse areas of computing including computer vision, databases, human–computer interaction, information security, image processing, information visualization and mining, as well as knowledge and information management to exchange ideas, discuss challenges, present their latest results and to advance research and development in the construction and application of visual information systems. Following previous conferences held in Melbourne (1996), San Diego (1997), Amsterdam (1999), Lyon (2000), Taiwan (2002), Miami (2003), San Francisco (2004) and Amsterdam (2005), the Ninth International Conference on visual Information Systems, vISUAL2007, was held in Shanghai, China, June 28–29, 2007. Over the years, the visual information systems paradigm continues to evolve, and the unrelenting exponential growth in the amount of digital visual data underlines the escalating importance of how such data are effectively managed and deployed. vISUAL2007 received 117 submissions from 15 countries and regions. Submitted full papers were reviewed by more than 60 international experts in the field. This volume collects 54 selected papers presented at vISUAL2007. Topics covered in these papers include image and video retrieval, visual biometrics, intelligent visual information processing, visual data mining, ubiquitous and mobile visual information systems, visual semantics, 2D/3D graphical visual data retrieval and applications of visual information systems.

关键词： Pattern Recognition image Processing and Computer vision Data Structures and Information Theory Information storage and retrieval Data Mining and Knowledge Discovery Information Systems Applications (incl. Internet)

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Illumination invariant video segmentation by hierarchical robust thresholding

Illumination invariant video segmentation by hierarchical ro...

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storage and retrieval for image and video databases vI

作者： Wei, Jie Drew, Mark S. Li, Ze-Nian School of Computing Science Simon Fraser University Vancouver BC V5A 1S6 Canada

Many methods for video segmentation rely upon the setting and tuning of thresholds for classifying interframe distances under various difference measures. An approach that has been used with some success has been to establish statistical measures for each new video and identify camera cuts as difference values far from the mean. For this type of strategy the mean and dispersion for some interframe distance measure must be calculated for each new video as a whole. Here we eliminate this statistical characterization step and at the same time allow for segmentation of streaming video by introducing a preprocessing step for illumination-invariance that concomitantly reduces input values to a uniform scale. The preprocessing step provides a solution to the problem that simple changes of illumination in a scene, such as an actor emerging from a shadow, can trigger a false positive transition, no matter whether intensity alone or chrominance is used in a distance measure. Our means of discounting lighting change for color constancy consists of the simple yet effective operation of normalizing each color channel to length (when viewed as a long length-N vector). We then reduce the dimensionally of color to two-dimensional chromaticity, with values which are in 0..1. Chromaticity histograms can be treated as images, and effectively low-pass filtered by wavelet-based reduction, followed by DCT and zonal coding. This results in an indexing scheme based on only 36 numbers, and lends itself to a binary search approach to transition detection. To this end we examine distributions for intra-clip and inter-clip distances separately, characterizing each using robust statistics, for temporal intervals from 32 frames to 1 frame by powers of 2. Then combining transition and non-transition distributions for each frame interval, we seek the valley between them, again robustly, for each threshold. Using the present method values of Precision and Recall are increased over previous methods.

关键词： image segmentation

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Progressive content-based retrieval from distributed image/video databases

Progressive content-based retrieval from distributed image/v...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Chung-Sheng Li v. Castelli L. Bergman IBM Thomas J. Watson Research Center Yorktown Heights NY USA

We describe the architecture and initial implementation of a content based retrieval mechanism from heterogeneous image archives. In particular, we propose an architecture to produce local representation of the images stored in heterogeneous archives and a progressive framework that reorganizes the image into a hierarchical representation both in the pixel domain and in the feature space. Consequently, search operations can be performed in a hierarchical fashion and thus significantly reduce the total amount of data that need to be processed. Dramatic speedup has been achieved for many search operations such as template matching, texture feature extraction, and histogram extraction.

关键词： Information retrieval image retrieval Content based retrieval Distributed databases image databases Pixel Histograms Data mining Satellites Biomedical imaging

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