data security and privacy are essential for transmitting, storing, and preserving medical images. This article provides a secure chaotic framework for medical imageencryption. The suggested technique has two stages: ...
详细信息
Reversible data Hiding (RDH) Technique aims in recovering back the original content from the marked media. The original image is desirable in some applications. Thus, RDH plays a vital role in such situations. Securin...
详细信息
ISBN:
(纸本)9781467358453
Reversible data Hiding (RDH) Technique aims in recovering back the original content from the marked media. The original image is desirable in some applications. Thus, RDH plays a vital role in such situations. Securing the multimedia content can be achieved by performing encryption. Transmission time is further decreased by compressing such encrypted images. The process of compression reduces the amount of data required for representing the image. The content owner thus encrypts the original image using Stream Cipher process. The encrypted image is then used as the media for hiding secret image. The embedded image can then be compressed using wavelet compression. The receiver does all the three processes in reverse for getting back the original image and the secret image. Thus the compressed image is first decompressed. Second, the data hiding key is employed to extract the secret message. Third, the encryption key is employed to decrypt and get back the original content. Thus this paper focuses on achieving better security and improved transmission rate.
The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression...
详细信息
ISBN:
(纸本)9780769550336
The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression techniques to store and transmit data in an apposite manner. compression schemes for images can be used to manage data of high sensitivity with less computational complexity. In this paper we suggest a novel algorithm for image compression and pattern matching called Difference Component Analysis (DCA). DCA extract the most relevant image feature components that identify the image. The DCA is based on the premise that matching images have minimal difference components. The experiment on DCA is done using more than 1000 human face images. The results show that the image can be compressed to a single decimal value and uses less computational steps. The concept can be applied for patternrecognitionencryption techniques.
The proceedings contain 24 papers. The topics discussed include: high-speed optical correlator with custom electronics interface design;coherent optical implementations of the fast Fourier transform and their comparis...
ISBN:
(纸本)9780819495396
The proceedings contain 24 papers. The topics discussed include: high-speed optical correlator with custom electronics interface design;coherent optical implementations of the fast Fourier transform and their comparison to the optical implementation of the quantum Fourier transform;adapted all-numerical correlator for face recognitionapplications;robust 3D reconstruction using LiDAR and N - visual image;optimized fusion method based on adaptation of the RMS time-frequency criterion for simultaneous compression and encryption of multiple images;a new morphology algorithm for shoreline extraction from DEM data;defining properties of speech spectrogram images to allow effective pre-processing prior to patternrecognition;an image hiding method based on cascaded iterative Fourier transform and public-key encryption algorithm;and enhanced information security employing orthogonal code, steganography, and joint transform correlation.
Reversible data Hiding (RDH) Technique aims in recovering back the original content from the marked media. The original image is desirable in some applications. Thus, RDH plays a vital role in such situations. Securin...
详细信息
Reversible data Hiding (RDH) Technique aims in recovering back the original content from the marked media. The original image is desirable in some applications. Thus, RDH plays a vital role in such situations. Securing the multimedia content can be achieved by performing encryption. Transmission time is further decreased by compressing such encrypted images. The process of compression reduces the amount of data required for representing the image. The content owner thus encrypts the original image using Stream Cipher process. The encrypted image is then used as the media for hiding secret image. The embedded image can then be compressed using wavelet compression. The receiver does all the three processes in reverse for getting back the original image and the secret image. Thus the compressed image is first decompressed. Second, the data hiding key is employed to extract the secret message. Third, the encryption key is employed to decrypt and get back the original content. Thus this paper focuses on achieving better security and improved transmission rate.
The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression...
详细信息
The development in communication and use of multimedia applications has created a remarkable demand for robust ways to store and transmit large databases of images. The current communication system demands compression techniques to store and transmit data in an apposite manner. compression schemes for images can be used to manage data of high sensitivity with less computational complexity. In this paper we suggest a novel algorithm for image compression and pattern matching called Difference Component Analysis (DCA). DCA extract the most relevant image feature components that identify the image. The DCA is based on the premise that matching images have minimal difference components. The experiment on DCA is done using more than 1000 human face images. The results show that the image can be compressed to a single decimal value and uses less computational steps. The concept can be applied for patternrecognitionencryption techniques.
Computer aided surgery is by sure a set of technologies that provide a real support to surgeons during their operational job. This includes - but it is not limited to - novel sensors and systems and software for data ...
详细信息
ISBN:
(纸本)9780819487469
Computer aided surgery is by sure a set of technologies that provide a real support to surgeons during their operational job. This includes - but it is not limited to - novel sensors and systems and software for data analysis and visualization. In particular the use of intraoperational probes is eased if the position of the probe within the operational field can be exactly calculated by the supporting software. Commercial systems have already been developed for this purpose but their complexity and cost reduces their usability for the majority of probes. This paper presents a simple approach to calculate the probe position within the operational field that requires a minimum cost.
Distributed Fiber Vibrant Sensor System is a new type of system, which could be used in long-distance, strong-EMI condition for monitoring vibration and sound signals. Position determination analysis toward this syste...
详细信息
ISBN:
(纸本)9780819487469
Distributed Fiber Vibrant Sensor System is a new type of system, which could be used in long-distance, strong-EMI condition for monitoring vibration and sound signals. Position determination analysis toward this system is popular in previous papers, but patternrecognition of the output signals of the sensor has been missed for a long time. This function turns to critical especially when it is used for real security project in which quick response to intrusion is a must. After pre-processing the output signal of the system, a MFCC-based approach is provided in this paper to extract features of the sensing signals, which could be used for patternrecognition in real project, and the approach is proved by large practical experiments and projects.
Linear classifiers based on computation over the real numbers R (e. g., with operations of addition and multiplication) denoted by (R, +, x), have been represented extensively in the literature of patternrecognition....
详细信息
ISBN:
(纸本)9780819487469
Linear classifiers based on computation over the real numbers R (e. g., with operations of addition and multiplication) denoted by (R, +, x), have been represented extensively in the literature of patternrecognition. However, a different approach to pattern classification involves the use of addition, maximum, and minimum operations over the reals in the algebra (R, +, v, Lambda). These pattern classifiers, based on lattice algebra, have been shown to exhibit superior information storage capacity, fast training and short convergence times, high pattern classification accuracy, and low computational cost. Such attributes are not always found, for example, in classical neural nets based on the linear inner product. In a special type of lattice associative memory (LAM), called a dendritic LAM or DLAM, it is possible to achieve noise-tolerant pattern classification by varying the design of noise or error acceptance bounds. This paper presents theory and algorithmic approaches for the computation of noise-tolerant lattice associative memories (LAMs) under a variety of input constraints. Of particular interest are the classification of nonergodic data in noise regimes with time-varying statistics. DLAMs, which are a specialization of LAMs derived from concepts of biological neural networks, have successfully been applied to pattern classification from hyperspectral remote sensing data, as well as spatial object recognition from digital imagery. The authors' recent research in the development of DLAMs is overviewed, with experimental results that show utility for a wide variety of pattern classification applications. Performance results are presented in terms of measured computational cost, noise tolerance, classification accuracy, and throughput for a variety of input data and noise levels.
暂无评论