A very low bit rate video coder decoder

Ankara : Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 1997.Thesis (Master's) -- Bilkent University, 1997.Includes bibliographical references leaves 81-85.Bostancı, Hakkı TunçM.S

Iris Information Management in Object-Relational Databases

Biometrics is a technology under development that has been enhanced by the increasing security concerns in organizations at all levels. Public agencies that employ this technology need to consult the biometric data efficiently and share them with other agencies. Hence the need for data models and standards that allow interoperability between systems and facilitate data searches. The objective of this work is to develop a generic architecture using object-relational database technology (ORDB), according to international standards, for identifying people by means of iris recognition. In addition, a model expressed in Unified Modeling Language (UML) class diagram where the domain data types defined for use in architecture is proposed. This architecture will allow interoperability between organizations efficiently and safely.XII Workshop Bases de Datos y Minería de Datos (WBDDM)Red de Universidades con Carreras en Informática (RedUNCI

Iris Information Management in Object-Relational Databases

Biometrics is a technology under development that has been enhanced by the increasing security concerns in organizations at all levels. Public agencies that employ this technology need to consult the biometric data efficiently and share them with other agencies. Hence the need for data models and standards that allow interoperability between systems and facilitate data searches. The objective of this work is to develop a generic architecture using object-relational database technology (ORDB), according to international standards, for identifying people by means of iris recognition. In addition, a model expressed in Unified Modeling Language (UML) class diagram where the domain data types defined for use in architecture is proposed. This architecture will allow interoperability between organizations efficiently and safely.XII Workshop Bases de Datos y Minería de Datos (WBDDM)Red de Universidades con Carreras en Informática (RedUNCI

Investigation of Different Video Compression Schemes Using Neural Networks

Image/Video compression has great significance in the communication of motion pictures and still images. The need for compression has resulted in the development of various techniques including transform coding, vector quantization and neural networks. this thesis neural network based methods are investigated to achieve good compression ratios while maintaining the image quality. Parts of this investigation include motion detection, and weight retraining. An adaptive technique is employed to improve the video frame quality for a given compression ratio by frequently updating the weights obtained from training. More specifically, weight retraining is performed only when the error exceeds a given threshold value. Image quality is measured objectively, using the peak signal-to-noise ratio versus performance measure. Results show the improved performance of the proposed architecture compared to existing approaches. The proposed method is implemented in MATLAB and the results obtained such as compression ratio versus signalto- noise ratio are presented

Exclusive-or preprocessing and dictionary coding of continuous-tone images.

The field of lossless image compression studies the various ways to represent image data in the most compact and efficient manner possible that also allows the image to be reproduced without any loss. One of the most efficient strategies used in lossless compression is to introduce entropy reduction through decorrelation. This study focuses on using the exclusive-or logic operator in a decorrelation filter as the preprocessing phase of lossless image compression of continuous-tone images. The exclusive-or logic operator is simply and reversibly applied to continuous-tone images for the purpose of extracting differences between neighboring pixels. Implementation of the exclusive-or operator also does not introduce data expansion. Traditional as well as innovative prediction methods are included for the creation of inputs for the exclusive-or logic based decorrelation filter. The results of the filter are then encoded by a variation of the Lempel-Ziv-Welch dictionary coder. Dictionary coding is selected for the coding phase of the algorithm because it does not require the storage of code tables or probabilities and because it is lower in complexity than other popular options such as Huffman or Arithmetic coding. The first modification of the Lempel-Ziv-Welch dictionary coder is that image data can be read in a sequence that is linear, 2-dimensional, or an adaptive combination of both. The second modification of the dictionary coder is that the coder can instead include multiple, dynamically chosen dictionaries. Experiments indicate that the exclusive-or operator based decorrelation filter when combined with a modified Lempel-Ziv-Welch dictionary coder provides compression comparable to algorithms that represent the current standard in lossless compression. The proposed algorithm provides compression performance that is below the Context-Based, Adaptive, Lossless Image Compression (CALIC) algorithm by 23%, below the Low Complexity Lossless Compression for Images (LOCO-I) algorithm by 19%, and below the Portable Network Graphics implementation of the Deflate algorithm by 7%, but above the Zip implementation of the Deflate algorithm by 24%. The proposed algorithm uses the exclusive-or operator in the modeling phase and uses modified Lempel-Ziv-Welch dictionary coding in the coding phase to form a low complexity, reversible, and dynamic method of lossless image compression

Iris Information Management in Object-Relational Databases

Biometrics is a technology under development that has been enhanced by the increasing security concerns in organizations at all levels. Public agencies that employ this technology need to consult the biometric data efficiently and share them with other agencies. Hence the need for data models and standards that allow interoperability between systems and facilitate data searches. The objective of this work is to develop a generic architecture using object-relational database technology (ORDB), according to international standards, for identifying people by means of iris recognition. In addition, a model expressed in Unified Modeling Language (UML) class diagram where the domain data types defined for use in architecture is proposed. This architecture will allow interoperability between organizations efficiently and safely.XII Workshop Bases de Datos y Minería de Datos (WBDDM)Red de Universidades con Carreras en Informática (RedUNCI