Huffman Method Research Articles

Optimize Image Steganography Based on Distinction Disparity Value and HMPSO to Ensure Confidentiality and Integrity

To secure the massive amounts of secret messages, the integrity and confidentiality challenges must be addressed. Pressing challenges in the context of a steganography system include security, imperceptibility, and capacity issues. There are trade‐offs between payload and security that have been neglected by researchers, as fixing one issue has been indicated to affect the other, and vice versa. To overcome these challenges, a new steganography scheme based on HMPSO and DDV was introduced. The HMPSO is short for Hénon map and particle swarm optimization, while DDV is short for distinction disparity value. The proposed scheme consisted of four phases with different contributions. The first phase was used to preprocess the secret messages and cover images. In this phase, the secret message has been compressed using the Huffman method. The second phase involved the embedding procedure. This phase consists of two different contributions HMPSO and DDV. The HMPSO is responsible for the optimal pixels’ selection. While the DDV is responsible for the embedding process. The third phase involves the extraction method. In extraction, the reverse processes of the previous steps are implemented. Different evaluation parameters have been used to validate and test the proposed scheme such as SSIM, PSNR, HVS, Histogram analysis, and chi‐square test. Based on the findings, the proposed scheme has solved the confidentiality and integrity challenges and provides a robust steganography system.

DIGITAL DATA SECURITY WITH APPLICATION OF CRYPTOGRAPHY AND DATA COMPRESSION TECHNIQUES

The need for digital data security is to ensure that the data and information we have are confidential and can only be accessed by authorized users. And no one can change the information in it, thus ensuring complete accuracy. The functions of data security are confidentiality, authentication, integrity, and anti-repudiation. Compression techniques are used to protect digital data because they aim to make less storage space and allow us to transfer more data over the internet. This study aims to plan to prove the application of a combination of 2 (two) techniques, namely compression and cryptography to digital data with the aim of increasing the security of the data. This research has the result that the compression technique of the Huffman method is the most effective in compressing digital data into the smallest file size compared to other compression methods. It can compressed the data size by around 30% (thirty percent) to 40% (forty percent) compared to the original data size. And coupled with data security with cryptographic encryption techniques so that files remain safe when transferred over the network.

Creation of a video data reliability assessment model for compression coding technology in the conditions of errors in the data transmission channel

The technology of compression coding of video data for information communication systems of the air segment is being studied. Distinctive features of the developed technology are the following: structural decomposition of the information space by structural feature; the use of a two-hierarchical scheme of statistical coding. A feature of the proposed technology is the use of a statistical approach in the process of forming the informational part of the codegram and the marker (identifier) of the code structure in the original code sequence. This makes it possible to create conditions for localizing the action of errors that occur in the process of video data delivery in the air segment info-communication systems. A model for evaluating the effectiveness of the proposed video data compression coding technology is created. A feature of the created model is the use of both quantitative and qualitative indicators of data distortions of the video information resource under the conditions of errors in the data transmission channels. A comparative analysis of the developed technology with lossless coding methods (Huffman method) and existing compression coding technologies built on the basis of the JPEG platform is carried out. The advantages of the proposed technology are the provision of localization of the action of errors due to the use of additional service information (identifiers) about the code structure, which is formed in the process of statistical coding of the data of the video information resource.

Research on the effectiveness of noise reduction when encoding a lossless speech signal

In the meantime, speech coding is one of the methods to represent the digital speech signal as in possible fewer bits value and to maintain the quality and its clearness. In omnipresent situations, encryption and examination of speech maintain a crucial role in various acoustic-based coding systems. This paper, using subband and Huffman coding technique, has been used for speech signals description to reduce the occupied by the speech data memory. The amplitude values of the taken speech are segregated after pre-processing, windowing and decomposition techniques. These data are converted into the frequency domain using discrete cosine transform (DCT). Then 90 foremost coefficients have been coded by Huffman method, they contain the most valuable information of speech signals. Signals are segregated then and subband coding techniques applied. To reconstruct the input speech, the taken speech is re-transformed in the form of time-domain applying through inverse discrete cosine transform (IDCT). This experiment is carried out by speech data at 8 kHz with 16 bits/per sample. The SNR (Signal to Noise Ratio) shows the efficiency of this applied technique.

A High-Throughput VLSI Architecture Design of Canonical Huffman Encoder

In this brief, a high-throughput Huffman encoder VLSI architecture based on the Canonical Huffman method is proposed to improve the encoding throughput and decrease the encoding time required by the Huffman code word table construction process. We proposed parallel computing architectures for frequency-statistical sorting and code-size computational sorting. This architecture results in a process of building a tree and assigning symbols that can be completed by scanning the data only once. This solves the problem of the low efficiency of the traditional algorithm, which needs to scan the data twice. Consequently, in addition to the advantages of the high compression ratio inherited from the Canonical Huffman, the proposed architecture has overridden advantages for a high parallelism processing capacity. The experimental results showed that the proposed architecture decreased the encoding time by 26.30% compared to the available Huffman encoder using the standard algorithm when encoding 256 8-bit symbols. Furthermore, the VLSI architecture could further decrease the encoding time when encoding more 8-bit symbols. In particular, when encoding 212,642 8-bit symbols, the proposed VLSI architecture could reduce the encoding time by 87.40%. Thus, compared with the traditional Huffman encoders, this brief achieved the improvement of coding efficiency.

COMPARATIVE ANALYSIS OF COMPACT METHODS REPRESENTATIONS OF GRAPHIC INFORMATION

The main characteristics of graphic information compression methods with losses and without losses (RLE, LZW, Huffman's method, DEFLATE, JBIG, JPEG, JPEG 2000, Lossless JPEG, fractal and Wawelet) are analyzed in the article. Effective transmission and storage of images in railway communication systems is an important task now. Because large images require large storage resources. This task has become very important in recent years, as the problems of information transmission by telecommunication channels of the transport infrastructure have become urgent. There is also a great need for video conferencing, where the task is to effectively compress video data - because the greater the amount of data, the greater the cost of transmitting information, respectively. Therefore, the use of image compression methods that reduce the file size is the solution to this task. The study highlights the advantages and disadvantages of compression methods. The comparative analysis the basic possibilities of compression methods of graphic information is carried out. The relevance lies in the efficient transfer and storage of graphical information, as big data requires large resources for storage. The practical significance lies in solving the problem of effectively reducing the data size by applying known compression methods.

Image Compression Using Swarm Intelligence

As a result of the development in multimedia technology and direct dealing with it in social media, it has led to interest in the techniques of compacting color images because of their importance at present. Since image compression enables the representation of color image data with the fewest number of bits, which reduces transmission time in the network and increases transmission speed. To ensure the compression process is performed without loss of data, the lossless compression methods are used because no data is lost during the compression process. In this research, a new system was presented to compress the color images with efficiency and high quality. Where the swarm intelligent methods were used, as well as hybridizing it with fuzzy using the Gustafson kessel fuzzy method to improve the clustering process and create new clustering methods with fuzzy swarm intelligence to obtain the best results. Swarm algorithms were used to perform the process of clustering the image data to be compressed and then obtaining a clustered data for this image data. In contrast, a lossless compression method was used to perform the encoding of this clustered data where the huffman method was used for encoding. Four methods were applied in this research to different color and lighting images. The PSO swarm intelligent was used, which in turn was hybridized with the Gustafson kessel fuzzy method to produce a new method for fuzzy particle swarm (FPSO), as well as the grey wolf optimization method GWO, which was hybridized with Gustafson kessel and obtained a new method, which is the fuzzy grey wolf optimizer FGWO, and the results were graded efficiently from the first to the fourth method, where the FGWO method with the huffman was the most efficient depending on the standards measurement that were calculated for all methods, the compression ratio was high in this new method, in addition to the standards of MSE, RMSE, PSNR, etc. among the important measurements of the compressing process.

Real-Time Lossless Compression for Ultrahigh-Density Synchrophasor and Point-on-Wave Data

Modern advanced phasor measurement units are developed with ultrahigh reporting rates to meet the demand for monitoring the power systems dynamics in detail. Due to the large volume of data, the communication and storage systems are seriously challenged with the presence of ultrahigh-density (UHD) synchrophasor and point-on-wave (POW) data. Therefore, it is an urgent task to compress the UHD data for more efficient communication and data storage. This article proposes several methods to compress the synchrophasor and POW data in a lossless manner. First, an improved time-series special compression (ITSSC) method is proposed to compress the UHD frequency data. Second, a delta-difference Huffman method is combined with the time-series special compression algorithm to compress the UHD phase angle data. Finally, a cyclical high-order delta modulation method is proposed to compress the UHD POW data. The proposed models are extensively tested and compared with different existing lossless compression algorithms using the field-collected synchrophasor and POW data at different reporting rates. The results indicate that the proposed algorithms are efficient in performing lossless compression for the UHD synchrophasor and POW data in real time.

Оценка матрицы пассажирских корреспонденций с использованием метода наименьших квадратов для калибровки гравитационной модели

The matrix of passenger correspondence plays a key role in many issues of planning and forecasting the development of the transport system. Usually, a gravitational model is used to evaluate the correspondence matrix. The specification and calibration method of the gravity model depends on what data is known from observations. In particular, if the volumes of departures and arrivals for each point and the average cost (duration) of the trip are known, then a gravitational model with an exponential gravity function is used, and the Hyman method is used to calibrate it. If the correspondence matrix is partially known, then a piecewise constant function can be taken as the gravity function and the Poisson method can be used for calibration. In this paper, we investigate the possibility of using the least squares method to calibrate a gravitational model with an exponential gravity function based on the observed correspondence matrix obtained on the basis of automated data collection on the online service of announcements about joint trips (carpooling). For such an observed correspondence matrix, a model correspondence matrix is calculated using the Huffman method and the least squares method. As a result, it was found that both methods produce models that approximate the observed data equally well.

Research on image compression technology based on Huffman coding

With the development of information technology, image has become the mainstream of information transmission. Compared with character, image contains more information, but because image and character need more storage capacity, it will occupy more bandwidth in network transmission. In order to transmit image information more quickly, image compression is a good choice. This paper is based on an eye of image compression. The method of image compression in this paper is that firstly, the image is filtered by wavelet transform to remove the redundant information in the image, and then the Huffman method is used to encode the image. The simulation results of JPEG format image show that the size of the image can be reduced in the same image effect.

IMPLEMENTASI DAN ANALISIS KOMPRESI HYBRID PADA CITRA MEDIS DIGITAL HASIL RONTGEN KANKER PAYUDARA

Digital image compression is an attempt to transform the data or symbols of composing digital images into data or other symbols without causing significant changes in the digital image to the human views. The goal is to reduce the redundancy of the data contained in the image so it can be stored or transmitted efficiently. Breast cancer is one of the greatest cancer cases in Indonesia which requires so many digital data x-rays. This research is intended to compress digital X-ray images of breast cancer with more efficient size without altering or reducing its information and it still can be assessed by human view. Using hybrid compression method, they are 2D DCT (Two Dimensional Discret Cosine Transform) and Huffman Method, Medical expert gave 3 of 4 rate when it reach 34.36% compression ratio with 40dB PSNR. This test result used 0 till 3 depth of zero in 2D DCT quantization process.

Dynamic Alternation of Huffman Codebooks for Sensor Data Compression

Signal compression is crucial for reducing the amount of communication, and hence power consumption of wireless sensors. Lossless compression techniques, such as Huffman coding, are often used in healthcare applications since they do not compromise the integrity of vital signals. Techniques that adapt to changing signal patterns have been proposed. However, most of them involve significant computation overhead or are too simple to maintain high compression rates under changing signal patterns. In this letter, we propose a technique that makes use of multiple codebooks, which are generated offline based on the signal context. In the applications we study, we observe that the symbols that compose a big variety of signals follow Laplacian distributions in which the spread changes over time. This can be effectively utilized to generate a set of codebooks. Then, appropriate codebooks are selected online depending on the currently measured spread, which ensures high compression efficiency and the adaptability to changing signal patterns. Our experiments on real-world medical datasets show that our approach is computationally very efficient, and exhibits competitive compression rates. Our proposed technique outperforms a state-of-the-art compression algorithm, FAS-LEC, in terms of average data reduction by 4.3%, while consuming a similar amount of energy. Compared to the adaptive Huffman method, which achieves near-optimal compression rates, our results indicate energy savings of 19% due to the reduced computational complexity, while the compression rate is improved by 0.6%.

Efficient Real-Time Lossless EMG Data Transmission to Monitor Pre-Term Delivery in a Medical Information System

An estimated 15 million babies are born prematurely every year worldwide, and suffer from disabilities. Appropriate care of these pre-term babies immediately after birth through telemedicine monitoring is vital. However, problems associated with a limited bandwidth and network overload due to the excessive size of the electromyography (EMG) signal impede the practical application of such medical information systems. Therefore, this research proposes an EMG uterine monitoring transmission solution (EUMTS), a lossless efficient real-time EMG transmission solution that solves such problems through efficient EMG data lossless compression. EMG data samples obtained from the Physionet PhysioBank database were used. Solution performance comparisons were conducted using Lempel-Ziv Welch (LZW) and Huffman methods, in addition to related researches. The LZW and Huffman methods showed CRs of 1.87 and 1.90, respectively, compared to 3.61 for the proposed algorithm. This was relatively high compared to related researches, even when considering that those researches were lossy whereas the proposed research was lossless. The results also showed that the proposed algorithm contributes to a reduction in battery consumption by reducing the wake-up time by 1470.6 ms. Therefore, EUMTS will contribute to providing an efficient wireless transmission environment for the prediction of pre-term delivery, enabling immediate interventions by medical professionals. Another novel point of EUMTS is that it is a lossless algorithm, which will prevent any misjudgement by clinicians because the data will not be distorted. Pre-term babies may receive point-of-care immediately after birth, preventing exposure to the development of disabilities.

EMBEDDED ZEROTREE WAVELET CODING WITH JOINT HUFFMAN AND ARITHMETIC CODING

Image compression is a task of reducing the image size without image quality degradation. It provides solution to both the problems of limited storage and long transmission time. This paper presents a method of combinational coding using Huffman and Arithmetic technique. The Embedded Zerotree Wavelet method which provides embedded bit stream is employed for image compression. The EZW symbols obtained are first coded using Huffman method. The Huffman bit stream is converted into byte stream and then into equivalent decimal. The final integer stream obtained is coded using Arithmetic coding. The proposed method of joint coding provides improved compression ratio as compared with Huffman coding alone.

Метод быстрого сжатия изображений без потерь

A suggested digital image compression method is characterized by simplicity of implementation and the lack of computing operations at the stage of prediction. Background: Miniature space watch facilities (small satellites) cannot provide a continuous data transmission because of the severely constrained requirements for energy resources usage efficiency that produces the necessity of new energy efficient low-cost digital images compression methods, which would not be inferior to the known multidigit digital images compression methods with high resolution but surpass them. Methods: The algorithm consists of the following procedures, splitting the digital images into binary images, predicting of each element of binary images being based on the theory of the conditional Markov processes with discrete states, and coding using any known algorithm (here, Huffman method is used). Results: To prove the efficiency of the proposed method, the compression of the Earth surface space pictures (group A) and photos (group B) is done. In each groupm, there were 50 onetype images. The known lossless compression algorithms such as PNG, JPEG-LS, JPEG 2000, BMF, Qlic, and ImageZero, are used as analogs. The obtained research results indicate that the proposed method performance and compression ratio comparable with analogues. Concluding Remarks: The suggested method has the following advantages: the capability of simultaneous binary images processing, the capability of digital images processing with digit capacity, and the lack of computational operations.

Analysis of advanced techniques of image processing based on automatic detection system and road signs recognition

This paper describes implementations of the Hough Circle Transform and the Radon Line Transform. The presented transforms were used to build a system for identify- ing road signs from selected images and recordings. This can be very important and espe- cially useful for monitoring and prevention in driver assistance systems. The design of our system assumed that the objects should be found automatically from images or video sequence. Furthermore, the detection was based on the shapes of common traffic signs which correspond to used transforms. Additionally, the Huffman method was applied to encode the data before being compared. Consequently, the traffic signs were matched directly with the Euclidean distance.

Establishment Threshold Value of Image Realization & Reconstruction of Stoppage Image using Picture Resemblance

In this paper, JPEG(Joint Photographic Experts Group) image data video decoding technique is presented, it is Huffman decoding method and fractal image method which is very complexive algorithm and the time required much it to implement this method and the first image is decoded to video frame image. This have defect of overlap decoding and transport work because of impossible to represent objective value of resemblance. The proposed method was calculated the mathematical absolute image resemblance and simplify the moving picture process to reducing the step of moving picture codefying. The results show that smoothed moving picture compared recent methods.

Direct Arc-Discharge Assisted Synthesis of C60H2(C3H5N): A cis-1-Pyrrolino C60 Fullerene Hydride with Unusual Redox Properties

By direct arc synthesis of C60H2(C3H5N) using a modified Krätschmer−Huffman method, it is demonstrated for the first time that exohedral fullerenes with large side groups can be formed under the arc and reactive gas atmosphere conditions. The thus formed novel pyrrolino fullerene hydride was comprehensively characterized by UV−vis, infrared (IR), Raman and nuclear magnetic resonance (NMR) and studied by means of electrochemistry and in situ electron spin resonance/visible-near infrared (ESR/Vis-NIR) spectroelectrochemistry. The detailed NMR and absorption spectroscopic studies show C60H2(C3H5N) as the fullerene hydride with a pyrrolino ring attached on the vicinal position of two hydrogen atoms. This first cycloaddition adduct of C60H2 gives rise to an unusual reversible dimerization of its anion radicals and a loss of cage hydrogen atoms at the third electron transfer. The spectroelectrochemical study confirms the formation of a [C60H2(C3H5N)]− radical and the diamagnetic state of [C60H2(C3H5N)] 2−. This study reveals a unique function of a carbide structure like Al4C3 and the presence of a reactive gas atmosphere with NH3 in the formation of such an exohedral pyrrolino structure C60H2(C3H5N).

Simple Compression Algorithm for Memoryless Laplacian Source Based on the Optimal Companding Technique

This paper has two achievements. The first aim of this paper is optimization of the lossy compression coder realized as companding quantizer with optimal compression law. This optimization is achieved by optimizing maximal amplitude for that optimal companding quantizer for Laplacian source. Approximate expression in closed form for optimal maximal amplitude is found. Although this expression is very simple and suitable for practical implementation, it satisfy optimality criterion for Lloyd-Max quantizer (for R >= 6 bits/sample). In the second part of this paper novel simple lossless compression method is presented. This method is much simpler than Huffman method, but it gives better results. Finally, at the end of the paper, we join optimal companding quantizer and lossless coding method together in one generalized compression method. This method is applied on the concrete still image and good results are obtained. Besides still images, this method also could be used for compression speech and bio-medical signals.

Overviews and Systematic Reviews on Low Back Pain

Letters20 May 2008Overviews and Systematic Reviews on Low Back PainJan M. Bjordal, MPT, PhD, Atle Klovning, MD, Rodrigo Alvaro B. Lopes-Martins, MPharm, PhD, Pål-Didrik Hoff Roland, MPharm, Jon Joensen, MPT, and Lars Slørdal, MD, PhDJan M. Bjordal, MPT, PhDFrom Bergen University College, 5009 Bergen, Norway; University of Oslo, 0318 Oslo, Norway; University of São Paulo, 05508-900 São Paulo, Brazil; St. Olavs Hospital, 7006 Trondheim, Norway; University of Bergen, 5018 Bergen, Norway; and Norwegian University of Science and Technology, 7489 Trondheim, Norway.Search for more papers by this author, Atle Klovning, MDFrom Bergen University College, 5009 Bergen, Norway; University of Oslo, 0318 Oslo, Norway; University of São Paulo, 05508-900 São Paulo, Brazil; St. Olavs Hospital, 7006 Trondheim, Norway; University of Bergen, 5018 Bergen, Norway; and Norwegian University of Science and Technology, 7489 Trondheim, Norway.Search for more papers by this author, Rodrigo Alvaro B. Lopes-Martins, MPharm, PhDFrom Bergen University College, 5009 Bergen, Norway; University of Oslo, 0318 Oslo, Norway; University of São Paulo, 05508-900 São Paulo, Brazil; St. Olavs Hospital, 7006 Trondheim, Norway; University of Bergen, 5018 Bergen, Norway; and Norwegian University of Science and Technology, 7489 Trondheim, Norway.Search for more papers by this author, Pål-Didrik Hoff Roland, MPharmFrom Bergen University College, 5009 Bergen, Norway; University of Oslo, 0318 Oslo, Norway; University of São Paulo, 05508-900 São Paulo, Brazil; St. Olavs Hospital, 7006 Trondheim, Norway; University of Bergen, 5018 Bergen, Norway; and Norwegian University of Science and Technology, 7489 Trondheim, Norway.Search for more papers by this author, Jon Joensen, MPTFrom Bergen University College, 5009 Bergen, Norway; University of Oslo, 0318 Oslo, Norway; University of São Paulo, 05508-900 São Paulo, Brazil; St. Olavs Hospital, 7006 Trondheim, Norway; University of Bergen, 5018 Bergen, Norway; and Norwegian University of Science and Technology, 7489 Trondheim, Norway.Search for more papers by this author, and Lars Slørdal, MD, PhDFrom Bergen University College, 5009 Bergen, Norway; University of Oslo, 0318 Oslo, Norway; University of São Paulo, 05508-900 São Paulo, Brazil; St. Olavs Hospital, 7006 Trondheim, Norway; University of Bergen, 5018 Bergen, Norway; and Norwegian University of Science and Technology, 7489 Trondheim, Norway.Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-148-10-200805200-00014 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail TO THE EDITOR:In a recent overview of systematic reviews and randomized trials of pharmacotherapy in low back pain, Chou and Huffman (1) concluded that there is good evidence that acetaminophen, nonsteroidal anti-inflammatory drugs (NSAIDs), and muscle relaxants provide moderate pain relief in acute low back pain. In the clinical practice guideline (2) in the same issue, the recommendations for acetaminophen and NSAIDs are extended to include chronic low back pain and tramadol, opioids, and benzodiazepines are recommended both in acute and chronic low back pain despite lack of “good” or even “fair” evidence. Chou and Huffman's method of reviewing ...