Search results for: Image database
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2108

Search results for: Image database

2078 A Formal Implementation of Database Security

Authors: Yun Bai

Abstract:

This paper is to investigate the impplementation of security mechanism in object oriented database system. Formal methods plays an essential role in computer security due to its powerful expressiveness and concise syntax and semantics. In this paper, both issues of specification and implementation in database security environment will be considered; and the database security is achieved through the development of an efficient implementation of the specification without compromising its originality and expressiveness.

Keywords: database security, authorization policy, logic basedspecification

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2077 Composite Relevance Feedback for Image Retrieval

Authors: Pushpa B. Patil, Manesh B. Kokare

Abstract:

This paper presents content-based image retrieval (CBIR) frameworks with relevance feedback (RF) based on combined learning of support vector machines (SVM) and AdaBoosts. The framework incorporates only most relevant images obtained from both the learning algorithm. To speed up the system, it removes irrelevant images from the database, which are returned from SVM learner. It is the key to achieve the effective retrieval performance in terms of time and accuracy. The experimental results show that this framework had significant improvement in retrieval effectiveness, which can finally improve the retrieval performance.

Keywords: Image retrieval, relevance feedback, wavelet transform.

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2076 A Case Study on Appearance Based Feature Extraction Techniques and Their Susceptibility to Image Degradations for the Task of Face Recognition

Authors: Vitomir Struc, Nikola Pavesic

Abstract:

Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.

Keywords: Biometrics, face recognition, appearance based methods, image degradations, the XM2VTS database.

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2075 Indexing and Searching of Image Data in Multimedia Databases Using Axial Projection

Authors: Khalid A. Kaabneh

Abstract:

This paper introduces and studies new indexing techniques for content-based queries in images databases. Indexing is the key to providing sophisticated, accurate and fast searches for queries in image data. This research describes a new indexing approach, which depends on linear modeling of signals, using bases for modeling. A basis is a set of chosen images, and modeling an image is a least-squares approximation of the image as a linear combination of the basis images. The coefficients of the basis images are taken together to serve as index for that image. The paper describes the implementation of the indexing scheme, and presents the findings of our extensive evaluation that was conducted to optimize (1) the choice of the basis matrix (B), and (2) the size of the index A (N). Furthermore, we compare the performance of our indexing scheme with other schemes. Our results show that our scheme has significantly higher performance.

Keywords: Axial Projection, images, indexing, multimedia database, searching.

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2074 Content-Based Image Retrieval Using HSV Color Space Features

Authors: Hamed Qazanfari, Hamid Hassanpour, Kazem Qazanfari

Abstract:

In this paper, a method is provided for content-based image retrieval. Content-based image retrieval system searches query an image based on its visual content in an image database to retrieve similar images. In this paper, with the aim of simulating the human visual system sensitivity to image's edges and color features, the concept of color difference histogram (CDH) is used. CDH includes the perceptually color difference between two neighboring pixels with regard to colors and edge orientations. Since the HSV color space is close to the human visual system, the CDH is calculated in this color space. In addition, to improve the color features, the color histogram in HSV color space is also used as a feature. Among the extracted features, efficient features are selected using entropy and correlation criteria. The final features extract the content of images most efficiently. The proposed method has been evaluated on three standard databases Corel 5k, Corel 10k and UKBench. Experimental results show that the accuracy of the proposed image retrieval method is significantly improved compared to the recently developed methods.

Keywords: Content-based image retrieval, color difference histogram, efficient features selection, entropy, correlation.

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2073 2D Spherical Spaces for Face Relighting under Harsh Illumination

Authors: Amr Almaddah, Sadi Vural, Yasushi Mae, Kenichi Ohara, Tatsuo Arai

Abstract:

In this paper, we propose a robust face relighting technique by using spherical space properties. The proposed method is done for reducing the illumination effects on face recognition. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients. First, an internal training illumination database is generated by computing face albedo and face normal from 2D images under different lighting conditions. Based on the generated database, we analyze the target face pixels and compare them with the training bootstrap by using pre-generated tiles. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other works, our technique requires no 3D face models for the training process and takes a single 2D image as an input. Experimental results on publicly available databases show that the proposed technique works well under severe lighting conditions with significant improvements on the face recognition rates.

Keywords: Face synthesis and recognition, Face illumination recovery, 2D spherical spaces, Vision for graphics.

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2072 A Methodology for Data Migration between Different Database Management Systems

Authors: Bogdan Walek, Cyril Klimes

Abstract:

In present days the area of data migration is very topical. Current tools for data migration in the area of relational database have several disadvantages that are presented in this paper. We propose a methodology for data migration of the database tables and their data between various types of relational database systems (RDBMS). The proposed methodology contains an expert system. The expert system contains a knowledge base that is composed of IFTHEN rules and based on the input data suggests appropriate data types of columns of database tables. The proposed tool, which contains an expert system, also includes the possibility of optimizing the data types in the target RDBMS database tables based on processed data of the source RDBMS database tables. The proposed expert system is shown on data migration of selected database of the source RDBMS to the target RDBMS.

Keywords: Expert system, fuzzy, data migration, database, relational database, data type, relational database management system.

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2071 Generation of Photo-Mosaic Images through Block Matching and Color Adjustment

Authors: Hae-Yeoun Lee

Abstract:

Mosaic refers to a technique that makes image by gathering lots of small materials in various colors. This paper presents an automatic algorithm that makes the photo-mosaic image using photos. The algorithm is composed of 4 steps: partition and feature extraction, block matching, redundancy removal and color adjustment. The input image is partitioned in the small block to extract feature. Each block is matched to find similar photo in database by comparing similarity with Euclidean difference between blocks. The intensity of the block is adjusted to enhance the similarity of image by replacing the value of light and darkness with that of relevant block. Further, the quality of image is improved by minimizing the redundancy of tiles in the adjacent blocks. Experimental results support that the proposed algorithm is excellent in quantitative analysis and qualitative analysis.

Keywords: Photo-mosaic, Euclidean distance, Block matching, Intensity adjustment.

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2070 XML Data Management in Compressed Relational Database

Authors: Hongzhi Wang, Jianzhong Li, Hong Gao

Abstract:

XML is an important standard of data exchange and representation. As a mature database system, using relational database to support XML data may bring some advantages. But storing XML in relational database has obvious redundancy that wastes disk space, bandwidth and disk I/O when querying XML data. For the efficiency of storage and query XML, it is necessary to use compressed XML data in relational database. In this paper, a compressed relational database technology supporting XML data is presented. Original relational storage structure is adaptive to XPath query process. The compression method keeps this feature. Besides traditional relational database techniques, additional query process technologies on compressed relations and for special structure for XML are presented. In this paper, technologies for XQuery process in compressed relational database are presented..

Keywords: XML, compression, query processing

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2069 A New Approach to Steganography using Sinc-Convolution Method

Authors: Ahmad R. Naghsh-Nilchi, Latifeh Pourmohammadbagher

Abstract:

Both image steganography and image encryption have advantages and disadvantages. Steganograhy allows us to hide a desired image containing confidential information in a covered or host image while image encryption is decomposing the desired image to a non-readable, non-comprehended manner. The encryption methods are usually much more robust than the steganographic ones. However, they have a high visibility and would provoke the attackers easily since it usually is obvious from an encrypted image that something is hidden! The combination of steganography and encryption will cover both of their weaknesses and therefore, it increases the security. In this paper an image encryption method based on sinc-convolution along with using an encryption key of 128 bit length is introduced. Then, the encrypted image is covered by a host image using a modified version of JSteg steganography algorithm. This method could be applied to almost all image formats including TIF, BMP, GIF and JPEG. The experiment results show that our method is able to hide a desired image with high security and low visibility.

Keywords: Sinc Approximation, Image Encryption, Sincconvolution, Image Steganography, JSTEG.

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2068 Grouping and Indexing Color Features for Efficient Image Retrieval

Authors: M. V. Sudhamani, C. R. Venugopal

Abstract:

Content-based Image Retrieval (CBIR) aims at searching image databases for specific images that are similar to a given query image based on matching of features derived from the image content. This paper focuses on a low-dimensional color based indexing technique for achieving efficient and effective retrieval performance. In our approach, the color features are extracted using the mean shift algorithm, a robust clustering technique. Then the cluster (region) mode is used as representative of the image in 3-D color space. The feature descriptor consists of the representative color of a region and is indexed using a spatial indexing method that uses *R -tree thus avoiding the high-dimensional indexing problems associated with the traditional color histogram. Alternatively, the images in the database are clustered based on region feature similarity using Euclidian distance. Only representative (centroids) features of these clusters are indexed using *R -tree thus improving the efficiency. For similarity retrieval, each representative color in the query image or region is used independently to find regions containing that color. The results of these methods are compared. A JAVA based query engine supporting query-by- example is built to retrieve images by color.

Keywords: Content-based, indexing, cluster, region.

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2067 A Universal Model for Content-Based Image Retrieval

Authors: S. Nandagopalan, Dr. B. S. Adiga, N. Deepak

Abstract:

In this paper a novel approach for generalized image retrieval based on semantic contents is presented. A combination of three feature extraction methods namely color, texture, and edge histogram descriptor. There is a provision to add new features in future for better retrieval efficiency. Any combination of these methods, which is more appropriate for the application, can be used for retrieval. This is provided through User Interface (UI) in the form of relevance feedback. The image properties analyzed in this work are by using computer vision and image processing algorithms. For color the histogram of images are computed, for texture cooccurrence matrix based entropy, energy, etc, are calculated and for edge density it is Edge Histogram Descriptor (EHD) that is found. For retrieval of images, a novel idea is developed based on greedy strategy to reduce the computational complexity. The entire system was developed using AForge.Imaging (an open source product), MATLAB .NET Builder, C#, and Oracle 10g. The system was tested with Coral Image database containing 1000 natural images and achieved better results.

Keywords: Content Based Image Retrieval (CBIR), Cooccurrencematrix, Feature vector, Edge Histogram Descriptor(EHD), Greedy strategy.

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2066 Blind Low Frequency Watermarking Method

Authors: Dimitar Taskovski, Sofija Bogdanova, Momcilo Bogdanov

Abstract:

We present a low frequency watermarking method adaptive to image content. The image content is analyzed and properties of HVS are exploited to generate a visual mask of the same size as the approximation image. Using this mask we embed the watermark in the approximation image without degrading the image quality. Watermark detection is performed without using the original image. Experimental results show that the proposed watermarking method is robust against most common image processing operations, which can be easily implemented and usually do not degrade the image quality.

Keywords: Blind, digital watermarking, low frequency, visualmask.

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2065 Database Modelling Using WSML in the Specification of a Banking Application

Authors: Omid Sharifi, Member, ACM, Zeki Bayram, Member, ACM

Abstract:

We demonstrate through a sample application, Ebanking, that the Web Service Modelling Language Ontology component can be used as a very powerful object-oriented database design language with logic capabilities. Its conceptual syntax allows the definition of class hierarchies, and logic syntax allows the definition of constraints in the database. Relations, which are available for modelling relations of three or more concepts, can be connected to logical expressions, allowing the implicit specification of database content. Using a reasoning tool, logic queries can also be made against the database in simulation mode.

Keywords: Semantic web, ontology, E-banking, database, WSML, WSMO, E-R diagram.

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2064 A Comparative Study of Image Segmentation using Edge-Based Approach

Authors: Rajiv Kumar, Arthanariee A. M.

Abstract:

Image segmentation is the process to segment a given image into several parts so that each of these parts present in the image can be further analyzed. There are numerous techniques of image segmentation available in literature. In this paper, authors have been analyzed the edge-based approach for image segmentation. They have been implemented the different edge operators like Prewitt, Sobel, LoG, and Canny on the basis of their threshold parameter. The results of these operators have been shown for various images.

Keywords: Edge Operator, Edge-based Segmentation, Image Segmentation, Matlab 10.4.

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2063 Data Migration between Document-Oriented and Relational Databases

Authors: Bogdan Walek, Cyril Klimes

Abstract:

Current tools for data migration between documentoriented and relational databases have several disadvantages. We propose a new approach for data migration between documentoriented and relational databases. During data migration the relational schema of the target (relational database) is automatically created from collection of XML documents. Proposed approach is verified on data migration between document-oriented database IBM Lotus/ Notes Domino and relational database implemented in relational database management system (RDBMS) MySQL.

Keywords: data migration, database, document-oriented database, XML, relational schema

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2062 Low Resolution Single Neural Network Based Face Recognition

Authors: Jahan Zeb, Muhammad Younus Javed, Usman Qayyum

Abstract:

This research paper deals with the implementation of face recognition using neural network (recognition classifier) on low-resolution images. The proposed system contains two parts, preprocessing and face classification. The preprocessing part converts original images into blurry image using average filter and equalizes the histogram of those image (lighting normalization). The bi-cubic interpolation function is applied onto equalized image to get resized image. The resized image is actually low-resolution image providing faster processing for training and testing. The preprocessed image becomes the input to neural network classifier, which uses back-propagation algorithm to recognize the familiar faces. The crux of proposed algorithm is its beauty to use single neural network as classifier, which produces straightforward approach towards face recognition. The single neural network consists of three layers with Log sigmoid, Hyperbolic tangent sigmoid and Linear transfer function respectively. The training function, which is incorporated in our work, is Gradient descent with momentum (adaptive learning rate) back propagation. The proposed algorithm was trained on ORL (Olivetti Research Laboratory) database with 5 training images. The empirical results provide the accuracy of 94.50%, 93.00% and 90.25% for 20, 30 and 40 subjects respectively, with time delay of 0.0934 sec per image.

Keywords: Average filtering, Bicubic Interpolation, Neurons, vectorization.

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2061 Face Recognition Using Discrete Orthogonal Hahn Moments

Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.

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2060 New Approach for Constructing a Secure Biometric Database

Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

Abstract:

The multimodal biometric identification is the combination of several biometric systems; the challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: Biometric databases, Multimodal biometrics, security authentication, Digital watermarking.

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2059 A System to Integrate and Manipulate Protein Database Using BioPerl and XML

Authors: Zurinahni Zainol, Rosalina Abdul Salam, Rosni Abdullah, Nur'Aini, Wahidah Husain

Abstract:

The size, complexity and number of databases used for protein information have caused bioinformatics to lag behind in adapting to the need to handle this distributed information. Integrating all the information from different databases into one database is a challenging problem. Our main research is to develop a tool which can be used to access and manipulate protein information from difference databases. In our approach, we have integrated difference databases such as Swiss-prot, PDB, Interpro, and EMBL and transformed these databases in flat file format into relational form using XML and Bioperl. As a result, we showed this tool can search different sizes of protein information stored in relational database and the result can be retrieved faster compared to flat file database. A web based user interface is provided to allow user to access or search for protein information in the local database.

Keywords: Protein sequence database, relational database, integrated database.

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2058 Prediction of a Human Facial Image by ANN using Image Data and its Content on Web Pages

Authors: Chutimon Thitipornvanid, Siripun Sanguansintukul

Abstract:

Choosing the right metadata is a critical, as good information (metadata) attached to an image will facilitate its visibility from a pile of other images. The image-s value is enhanced not only by the quality of attached metadata but also by the technique of the search. This study proposes a technique that is simple but efficient to predict a single human image from a website using the basic image data and the embedded metadata of the image-s content appearing on web pages. The result is very encouraging with the prediction accuracy of 95%. This technique may become a great assist to librarians, researchers and many others for automatically and efficiently identifying a set of human images out of a greater set of images.

Keywords: Metadata, Prediction, Multi-layer perceptron, Human facial image, Image mining.

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2057 Stroke Extraction and Approximation with Interpolating Lagrange Curves

Authors: Bence Kővári, ZSolt Kertész

Abstract:

This paper proposes a stroke extraction method for use in off-line signature verification. After giving a brief overview of the current ongoing researches an algorithm is introduced for detecting and following strokes in static images of signatures. Problems like the handling of junctions and variations in line width and line intensity are discussed in detail. Results are validated by both using an existing on-line signature database and by employing image registration methods.

Keywords: Stroke extraction, spline fitting, off-line signatureverification, image registration.

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2056 A New Approach to Face Recognition Using Dual Dimension Reduction

Authors: M. Almas Anjum, M. Younus Javed, A. Basit

Abstract:

In this paper a new approach to face recognition is presented that achieves double dimension reduction, making the system computationally efficient with better recognition results and out perform common DCT technique of face recognition. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results change with change in face image resolution and provide optimal results when arriving at a certain resolution level. In the proposed model of face recognition, initially image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to increased computational speed and feature extraction potential of Discrete Cosine Transform (DCT), it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A tradeoff between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL , Yale and EME color database.

Keywords: Biometrics, DCT, Face Recognition, Illumination, Computation, Feature extraction.

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2055 Face Image Coding Using Face Prototyping

Authors: Jaroslav Polec, Lenka Krulikovská, Natália Helešová, Tomáš Hirner

Abstract:

In this paper we present a novel approach for face image coding. The proposed method makes a use of the features of video encoders like motion prediction. At first encoder selects appropriate prototype from the database and warps it according to features of encoding face. Warped prototype is placed as first I frame. Encoding face is placed as second frame as P frame type. Information about features positions, color change, selected prototype and data flow of P frame will be sent to decoder. The condition is both encoder and decoder own the same database of prototypes. We have run experiment with H.264 video encoder and obtained results were compared to results achieved by JPEG and JPEG2000. Obtained results show that our approach is able to achieve 3 times lower bitrate and two times higher PSNR in comparison with JPEG. According to comparison with JPEG2000 the bitrate was very similar, but subjective quality achieved by proposed method is better.

Keywords: Triangulation, H.264, Model-based coding, Average face

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2054 A Quantum Algorithm of Constructing Image Histogram

Authors: Yi Zhang, Kai Lu, Ying-hui Gao, Mo Wang

Abstract:

Histogram plays an important statistical role in digital image processing. However, the existing quantum image models are deficient to do this kind of image statistical processing because different gray scales are not distinguishable. In this paper, a novel quantum image representation model is proposed firstly in which the pixels with different gray scales can be distinguished and operated simultaneously. Based on the new model, a fast quantum algorithm of constructing histogram for quantum image is designed. Performance comparison reveals that the new quantum algorithm could achieve an approximately quadratic speedup than the classical counterpart. The proposed quantum model and algorithm have significant meanings for the future researches of quantum image processing.

Keywords: Quantum Image Representation, Quantum Algorithm, Image Histogram.

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2053 Modified Vector Quantization Method for Image Compression

Authors: K.Somasundaram, S.Domnic

Abstract:

A low bit rate still image compression scheme by compressing the indices of Vector Quantization (VQ) and generating residual codebook is proposed. The indices of VQ are compressed by exploiting correlation among image blocks, which reduces the bit per index. A residual codebook similar to VQ codebook is generated that represents the distortion produced in VQ. Using this residual codebook the distortion in the reconstructed image is removed, thereby increasing the image quality. Our scheme combines these two methods. Experimental results on standard image Lena show that our scheme can give a reconstructed image with a PSNR value of 31.6 db at 0.396 bits per pixel. Our scheme is also faster than the existing VQ variants.

Keywords: Image compression, Vector Quantization, Residual Codebook.

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2052 A New Technique for Progressive ECG Transmission using Discrete Radon Transform

Authors: Amine Naït-Ali

Abstract:

The aim of this paper is to present a new method which can be used for progressive transmission of electrocardiogram (ECG). The idea consists in transforming any ECG signal to an image, containing one beat in each row. In the first step, the beats are synchronized in order to reduce the high frequencies due to inter-beat transitions. The obtained image is then transformed using a discrete version of Radon Transform (DRT). Hence, transmitting the ECG, leads to transmit the most significant energy of the transformed image in Radon domain. For decoding purpose, the receptor needs to use the inverse Radon Transform as well as the two synchronization frames. The presented protocol can be adapted for lossy to lossless compression systems. In lossy mode we show that the compression ratio can be multiplied by an average factor of 2 for an acceptable quality of reconstructed signal. These results have been obtained on real signals from MIT database.

Keywords: Discrete Radon Transform, ECG compression, synchronization.

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2051 Image Indexing Using a Color Similarity Metric based on the Human Visual System

Authors: Angelo Nodari, Ignazio Gallo

Abstract:

The novelty proposed in this study is twofold and consists in the developing of a new color similarity metric based on the human visual system and a new color indexing based on a textual approach. The new color similarity metric proposed is based on the color perception of the human visual system. Consequently the results returned by the indexing system can fulfill as much as possibile the user expectations. We developed a web application to collect the users judgments about the similarities between colors, whose results are used to estimate the metric proposed in this study. In order to index the image's colors, we used a text indexing engine to facilitate the integration of visual features in a database of text documents. The textual signature is build by weighting the image's colors in according to their occurrence in the image. The use of a textual indexing engine, provide us a simple, fast and robust solution to index images. A typical usage of the system proposed in this study, is the development of applications whose data type is both visual and textual. In order to evaluate the proposed method we chose a price comparison engine as a case of study, collecting a series of commercial offers containing the textual description and the image representing a specific commercial offer.

Keywords: Color Extraction, Content-Based Image Retrieval, Indexing

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2050 Object Identification with Color, Texture, and Object-Correlation in CBIR System

Authors: Awais Adnan, Muhammad Nawaz, Sajid Anwar, Tamleek Ali, Muhammad Ali

Abstract:

Needs of an efficient information retrieval in recent years in increased more then ever because of the frequent use of digital information in our life. We see a lot of work in the area of textual information but in multimedia information, we cannot find much progress. In text based information, new technology of data mining and data marts are now in working that were started from the basic concept of database some where in 1960. In image search and especially in image identification, computerized system at very initial stages. Even in the area of image search we cannot see much progress as in the case of text based search techniques. One main reason for this is the wide spread roots of image search where many area like artificial intelligence, statistics, image processing, pattern recognition play their role. Even human psychology and perception and cultural diversity also have their share for the design of a good and efficient image recognition and retrieval system. A new object based search technique is presented in this paper where object in the image are identified on the basis of their geometrical shapes and other features like color and texture where object-co-relation augments this search process. To be more focused on objects identification, simple images are selected for the work to reduce the role of segmentation in overall process however same technique can also be applied for other images.

Keywords: Object correlation, Geometrical shape, Color, texture, features, contents.

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2049 A Middleware System between WEB and Database Servers

Authors: Mohammad H. Abu-Arqoub, Ihab S. Serhed, Waheeb A. Abu-Dawwas, Rashid M. Al-Azzeh

Abstract:

This paper aims at improving web server performance by establishing a middleware layer between web and database servers, which minimizes the overload on the database server. A middleware system has been developed as a service mainly to improve the performance. This system manages connection accesses in a way that would result in reducing the overload on the database server. In addition to the connection management, this system acts as an object-oriented model for best utilization of operating system resources. A web developer can use this Service Broker to improve web server performance.

Keywords: Database server, Improve performance, Middleware, Web server.

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