Run-length Encoding Research Articles

Compressing Optimal Paths with Run Length Encoding

We introduce a novel approach to Compressed Path Databases, space efficient oracles used to very quickly identify the first edge on a shortest path. Our algorithm achieves query running times on the 100 nanosecond scale, being significantly faster than state-of-the-art first-move oracles from the literature. Space consumption is competitive, due to a compression approach that rearranges rows and columns in a first-move matrix and then performs run length encoding (RLE) on the contents of the matrix. One variant of our implemented system was, by a convincing margin, the fastest entry in the 2014 Grid-Based Path Planning Competition. We give a first tractability analysis for the compression scheme used by our algorithm. We study the complexity of computing a database of minimum size for general directed and undirected graphs. We find that in both cases the problem is NP-complete. We also show that, for graphs which can be decomposed along articulation points, the problem can be decomposed into independent parts, with a corresponding reduction in its level of difficulty. In particular, this leads to simple and tractable algorithms with linear running time which yield optimal compression results for trees.

Gray-Scale Image Compression Techniques: A Review

Multimedia data are large in size as compared to the plain-text data. And hence to transmit them over a low-bandwidth communication channel, it needs to be compressed. In this paper, focus is on compressing gray-scale images. Here two types of compression techniques are explained: Lossy and Lossless. Within lossy techniques, there are three techniques: Fractal encoding, Discrete Cosine Transform (DCT), and Discrete Wavelet Transform (DWT). And Following are lossless techniques: Arithmatic Encoding, Run Length Encoding (RLE), and Huffman Encoding. The efficiency of compression process is estimated using Compression Ratio (C.R.) and the quality of reconstructed image which is generated after decompression process is calculated using Peak-Signal-to-Noise Ratio (P.S.N.R.). General Terms Image Compression, Lossless, Lossy

Multi-Bit Data Hiding Scheme for Compressing Secret Messages

The goal of data hiding techniques usually considers two issues, embedding capacity and image quality. Consequently, in order to achieve high embedding capacity and good image quality, a data hiding scheme combining run-length encoding (RLE) with multi-bit embedding is proposed in this paper. This work has three major contributions. First, the embedding capacity is increased 62% because the secret message is compressed before embedding into the cover image. Secondly, the proposed scheme keeps the multi-bit generalized exploiting modification direction (MGEMD) characteristics, which are effective to reduce modified pixels in the cover image and to maintain good stego image quality. Finally, the proposed scheme can prevent modern steganalysis methods, such as RS steganalysis and SPAM (subtractive pixel adjacency matrix), and is compared to MiPOD (minimizing the power of the optimal detector) scheme. From our simulation results and security discussions, we have the following results: First, there are no perceivable differences between the cover images and stego images from human inspection. For example, the average PSNR of stego images is about 44.61 dB when the secret message (80,000 bits) is embedded for test cover images (such as airplane, baboon, Lena) of size 512×512. Secondly, Appl. Sci. 2015, 5 1034 on average, 222,087 pixels were not modified after embedding for the cover image. That is to say, 12% less pixels are modified as compared to the MGEMD method. From the performance discussions, the proposed scheme achieves high embedding capacity and good image quality, but also maintains stego image security.

English

In this paper we present a new lossless audio coding algorithm using Burrows-Wheeler Transform (BWT) and Run Length Encoding (RLE).Audio signals used are assumed to be of floating point values. The BWT is applied to the audio signals to get the transformed coefficients and then these resulting coefficients are better compressed using Run Length Encoding. Two entropy coding are used which are Run Length Encoding and Huffman coding. Proposed compression algorithm is experimented and analyzed for two different stereo type audio signals. Compression ratio and Bit rate for audio coding has been used as a comparison parameter for proposed audio coding algorithm. Experimental result shows that the lossless audio coding algorithm outperforms other lossless audio coding methods; using combined Burrows Wheeler Transform & Move to front coding method ,using combined Burrows Wheeler Transform and Huffman coding method, and using Burrows Wheeler Transform ,Move to front coding method & Run Length Encoding method.

Workload prediction using run‐length encoding for runtime processor power management

In processor power management research, workload prediction is a requisite for adjusting frequency without performance loss, and previous studies have proposed various prediction algorithms. Among them, methods based on the workload history table are lightweight and have high prediction accuracy for a variable workload. However, such prediction algorithms lose their prediction accuracy in the case of repeated workload. An improved workload prediction method using run-length encoding is proposed, which handles workload repetition. Evaluation results show that the proposed algorithm improves the prediction of repeated workload by up to 14% and also improves 4% of energy saving.

Compression and Comparison of ECG Signals using DWT and DWPT

The work here attempts to incorporate the power of frequency domain tools like wavelets and wavelet packets for aiding data compression using runlength encoding. An attempt is made here to compare between the performance of wavelets and wavelet packets for data compression. The DWT is performed in one level with sym8, the coefficients are threshold by hard rule and encoding is done by zero run length. In case of DWPT the best tree is selected from level 8 decomposition based on maximum energy content in them and out of that sub bands, best bands are selected based on SVD.

Compressing optimal paths with run length encoding

We introduce a novel approach to Compressed Path Databases, space efficient oracles used to very quickly identify the first edge on a shortest path. Our algorithm achieves query running times on th...

Implementation of Health Monitoring System using Mixed Environment

Background: Research shows that the health care cost per capita have grown 2.4 percent faster than the gross domestic product (GDP) since 1970. The aim of this paper is to present a useful model of wireless system that can combine both hardware and software environments and it can also integrate with other technologies or infrastructure at a low cost, which can be used for the patient monitoring system. Methods: The biomedical sensor which is attached to the patient, will read analog data. The recorded data will be converted digitally by using Analog to Digital Converter (ADC) and a FPGA transmitter will be used to send this data to Phase Shift Keying (PSK) transmitter. The modulated data will be received by PSK receiver and another FPGA receiver will be used to get the data back on the system. For behavioural modelling Verilog hardware descriptive language is used to provide a high level abstraction and language constructions. And the Simulink software is used to provide a high-level mathematical modelling condition for digital communication system which can be used for the verification and algorithm development.The important modules implemented for the transmitter and receiver FPGA are bus interfacing, compression and the data framing. Findings: A short range wireless health monitoring wireless system is modelled by using a mixed software and hardware simulation environment.At all the stages of the hardware and software designs, different types of languages like Verilog HDL codes and MATLAB used to verify the operation of the modules. The behavioural HDL designed of the FPGA transmitter and receiver will be interfaced with the RF Simulink models of PSK transmitter and receiver by using System Generator (Sysgen) tool that acts as the converter simulator. A realistic design model of health monitoring system is implemented which can be used for future hardware design. Compression and framing are the two main operations used in the transmitter side. Data compression is implemented by Run-Length Encoding method and for data framing high data link control protocol has been used. The unique features of this models simulation are low cost, less complexity, low power dissipation and efficient data transmission. Finally the FPGA based healthcare system allows us to change the design configurations or up gradation of the system based on the requirements. Conclusion: In this paper distributed simulation approach is used for designing the health monitoring system which allows checking the specification of design at all the stages. Simulation by HDL and Simulink mixed models in not the objective of this work, but to prove that realistic design is possible for future health care system design.

New Approach in E-mail Based Text Steganography

In this study combination of lossless compression techniques and Vigenere cipher was used in text steganography that makes use of email addresses to be the keys to reconstruct the secret message which has been embedded into the email text. After selecting the cover text that has highest repetition pattern regarding to the secret message the distance matrix was formed. The members of distance matrix were compressed by following lossless compression algorithms as in written sequence; Run Length Encoding (RLE) + Burrows Wheeler Transform (BWT) + Move to Forward (MTF) + Run Length Encoding + Arithmetic Encoding (AE). Later on Latin Square was used to form stego key 1and then Vigenere table was used to increase complexity of extracting stego key 1. Final step was to choose e-mail addresses by using stego key 1 and stego key 2to embed secret message into forward e-mail platform. The experimental results showed that proposed method has reasonable performance with high complexity.

Lossy Image Compression Using Multiwavelet Transform for Wireless Transmission

The performance of the wavelets within the field of image process is standard. Multiwavelets is the next step in riffle theory and it takes the performance of wavelets to the next level. In this work the performance of the Integer Multiwavelet transform (IMWT) for lossy compression has been studied. The Proposed IMWT shows sensible performance in lossy reconstruction of the images than that of Existing lossy reconstruction. This work utilizes the performance of the Proposed IMWT for lossy compression of images with encoding techniques like Magnitude set coding and Run Length Encoding. The transform coefficients are unit coded by means of Magnitude set coding and run length coding techniques which in turn results with low bits. The transform coefficient matrix is coded on not taking under consideration of the sign values using the Magnitude Set--Variable Length Integer illustration. The sign data of the coefficients is coded as bit plane with zero thresholds. This Bit plane may be used as it is or coded to scale back the bits per pixels. The Simulation was exhausted using Matlab.

Better bitmap performance with Roaring bitmaps

SummaryBitmap indexes are commonly used in databases and search engines. By exploiting bit‐level parallelism, they can significantly accelerate queries. However, they can use much memory, and thus, we might prefer compressed bitmap indexes. Following Oracle's lead, bitmaps are often compressed using run‐length encoding (RLE). Building on prior work, we introduce the Roaring compressed bitmap format: it uses packed arrays for compression instead of RLE. We compare it to two high‐performance RLE‐based bitmap encoding techniques: Word Aligned Hybrid compression scheme and Compressed ‘n’ Composable Integer Set. On synthetic and real data, we find that Roaring bitmaps (1) often compress significantly better (e.g., 2×) and (2) are faster than the compressed alternatives (up to 900× faster for intersections). Our results challenge the view that RLE‐based bitmap compression is best. Copyright © 2015 John Wiley & Sons, Ltd.

Fast calculation of computer-generated hologram using run-length encoding based recurrence relation.

Computer-Generated Holograms (CGHs) can be generated by superimposing zoneplates. A zoneplate is a grating that can concentrate an incident light into a point. Since a zoneplate has a circular symmetry, we reported an algorithm that rapidly generates a zoneplate by drawing concentric circles using computer graphic techniques. However, random memory access was required in the algorithm and resulted in degradation of the computational efficiency. In this study, we propose a fast CGH generation algorithm without random memory access using run-length encoding (RLE) based recurrence relation. As a result, we succeeded in improving the calculation time by 88%, compared with that of the previous work.

악보인식 전처리를 위한 강건한 오선 두께와 간격 추정 방법

이 논문에서는 모바일 기기상에서 카메라기반 악보인식을 위한 오선 두께와 오선 간격을 추정하는 전처리 기술을 제안한다. 캡쳐된 영상은 조명이나, 흐려짐, 저해상도 등의 많은 왜곡으로 인해 인식에 어려움이 있다. 특히 복잡한 배경을 가지고 있는 악보 영상인식의 경우 더욱 그렇다. 악보 기호 인식에서 오선 두께와 오선 간격은 인식에 큰 영향을 끼친다. 이들 정보는 이진화에도 사용되는데, 복잡한 배경을 가지고 있는 경우 일반적인 이진 영상은 오선 두께와 간격을 추정하는데 만족스럽지 못하다. 따라서 우리는 에지영상에서 런-길이 엔코딩 기술을 이용해 오선 두께와 간격 추정하는 강건한 알고리즘을 제안한다. 제안된 방법은 2단계로 구성되어 있다. 첫 번째 단계는 소벨 연산자에 의해 영역별로 에지 영상을 기반으로 오선 두께와 간격을 추정한다. 각 에지 영상의 열은 런-길이 엔코딩 알고리즘에 의해 기술된다. 두 번째 단계는 안정한 경로 알고리즘을 이용한 오선 검출과 오선 위치를 추적하는 적응적 LTH알고리즘을 이용한 오선 제거이다. 실험결과 복잡한 영상의 경우에도 강건함과 높은 인식률을 보였다. In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.

Fast Retrieval with Column Store using RLE Compression Algorithm

Column oriented database have continued to grow over the past few decades. C-Store, Vertica Monet DB and Lucid DB are popular open source column oriented database. Columnstore in a nutshell, store each attribute values belonging to same column contiguously. Since column data is uniform type therefore, there are some opportunities for storage size optimization in Column-store, many renowned compression schemes such as RLE & LZW that make use of similarity of adjacent data to compress. Good Compression can also be achieved using bitmap index by order of magnitude through the sorting. The Run Length Encoding works best for the columns of ordered data, or data with few distinct values. This ensures long runs of identical values which RLE compresses quite well. In this paper we have put an effort to build a simulation of Column-Store and applied the best bitmap compression technique RLE which further improves the retrieval time. General Terms Your general terms must be any term which can be used for general classification of the submitted material such as Pattern Recognition, Security, Algorithms et. al.

Run-Length Encoding Graphic Rules Applied to DNA-Coded Images and Animation Editable by Polymerase Chain Reactions

We previously proposed novel designs for artificial genes as media for storing digitally compressed image data, specifically for biocomputing by analogy to natural genes mainly used to encode proteins. A run-length encoding (RLE) rule had been applied in DNA-based image data processing, to form coding regions, and noncoding regions were created as space for designing biochemical editing. In the present study, we apply the RLE-based image-coding rule to creation of DNAbased animation. This article consisted of three parts: (i) a theoretical review of RLE-based image coding by DNA, (ii) a technical proposal for biochemical editing of DNA-coded images using the polymerase chain reaction, and (iii) a minimal demonstration of DNAbased animation using simple model images encoded on short DNA molecules.

Random Access to Grammar-Compressed Strings and Trees

Grammar-based compression, where one replaces a long string by a small context-free grammar that generates the string, is a simple and powerful paradigm that captures (sometimes with slight reduction in efficiency) many of the popular compression schemes, including the Lempel--Ziv family, run-length encoding, byte-pair encoding, Sequitur, and Re-Pair. In this paper, we present a novel grammar representation that allows efficient random access to any character or substring without decompressing the string. Let $S$ be a string of length $N$ compressed into a context-free grammar $\mathcal{S}$ of size $n$. We present two representations of $\mathcal{S}$ achieving $O(\log N)$ random access time, and either $O(n\cdot\alpha_k(n))$ construction time and space on the pointer machine model, or $O(n)$ construction time and space on the RAM. Here, $\alpha_k(n)$ is the inverse of the $k$th row of Ackermann's function. Our representations also efficiently support decompression of any substring in $S$: we can decompres...

A Memory Efficient DFA Using Compression and Pattern Segmentation

Abstract The role of network security systems such as network intrusion detection system (NIDS) has become more important. The regular expression (a.k.a. regex) matching algorithm used for inspecting the payloads of packets is one of the most intensive tasks in NIDS. When multiple regular expressions are processed together, the corresponding Deterministic Finite Automata (DFA) becomes so complicated and needs a large amount of memory. In this paper, we propose a memory efficient parallel compatible DFA algorithm that uses the techniques of compression and pattern segmentation to reduce the memory usage. Extended from PFAC (Parallel Failureless-AC) algorithm4, the proposed compressed and segmented DFA (CSDFA) needs less numbers of states and transitions than δFA. Without considering the leading symbols “.*” in the regular expressions, the transition table can be compressed very efficiently by the run-length encoding. The number of transitions in CSDFA is about a half of the transitions needed in δFA, and uses only 74% of the memory consumed by δFA. Based on our experiments, the throughput of the proposed CSDFA is also much better than δFA.

State Transition Based Embedding in Cepstrum Domain for Audio Copyright Protection

ABSTRACTIn this paper, we propose a new state transition based embedding (STBE) technique for audio watermarking with high fidelity. Furthermore, we propose a new correlation based encoding (CBE) scheme for binary logo image in order to enhance the payload capacity. The result of CBE is also compared with standard run-length encoding (RLE) compression and Huffman schemes. Most of the watermarking algorithms are based on modulating selected transform domain feature of an audio segment in order to embed given watermark bit. In the proposed STBE method instead of modulating feature of each and every segment to embed data, our aim is to retain the default value of this feature for most of the segments. Thus, a high quality of watermarked audio is maintained. Here, the difference between the mean values (Mdiff) of insignificant complex cepstrum transform (CCT) coefficients of down-sampled subsets is selected as a robust feature for embedding. Mdiff values of the frames are changed only when certain conditions are met. Hence, almost 50% of the times, segments are not changed and still STBE can convey watermark information at receiver side. STBE also exhibits a partial restoration feature by which the watermarked audio can be restored partially after extraction of the watermark at detector side. The psychoacoustic model analysis showed that the noise-masking ratio (NMR) of our system is less than −10dB. As amplitude scaling in time domain does not affect selected insignificant CCT coefficients, strong invariance towards amplitude scaling attacks is also proved theoretically. Experimental results reveal that the proposed watermarking scheme maintains high audio quality and are simultaneously robust to general attacks like MP3 compression, amplitude scaling, additive noise, re-quantization, etc.

Feature-Based Object Location of IC Pins by Using Fast Run Length Encoding BLOB Analysis

Feature-Based Object Location of IC Pins by Using Fast Run Length Encoding BLOB Analysis

A LOW POWER NEW DATA COMPRESSION ALGORITHM FOR WIRE/WIRELESS SENSOR NETWORKS USING K-RLE

In this project, we propose and evaluate a new data compression algorithm inspired from Run Length Encoding called K-RLE which means RLE with a K-Precision. This increases the ratio compression compared to RLE. In order to improve the compression results with different statistics of data sources. Here we want to introduce in-network processing technique in order to save energy. In-network processing techniques allow the reduction of the amount of data to be transmitted. The well known in-network processing technique is data compression and/or data aggregation. Data compression is a process that reduces the amount of data in order to reduce data transmitted and/or decreases transfer time because the size of the data is reduced.