Run-length Coding Research Articles

High performance decoding aware FPGA bit-stream compression using RG codes

FPGA design for complex applications need high capacity of configuration memory. To fullfil the large memory requirement, higher end FPGAs are required and it leads to higher cost. In order to reduce the cost constraint, bit-stream compression is prominently involved to reduce the bit-stream size and the memory requirement of FPGA configuration. In this paper new code compression techniques are proposed with minimum cost. The proposed code compression techniques RG-1 and RG-2 codes are designed based on the combination of run length and Golomb coding. The proposed RG codes overcome the limitation of both run length and Golomb coding techniques. The main contribution of this work is to analyze the proposed work in terms of number of 1’s, number of transitions and size of compressed bits. The comparison result shows that the RG code is more robust when compared to other traditional code compression techniques. The results shows that CR improvement of 9 and 5% compare with RLE for the RG-1 and RG-2 respectively and CR improvement of 7 and 2% compare with golomb for the RG-1 and RG-2 respectively.

Lattice Codes for Deletion and Repetition Channels

The construction of deletion codes for the editing metric is reduced to the construction of codes over the integers for the Manhattan metric by run length coding. The latter codes are constructed by expurgation of lattices’ translates. These lattices, in turn, are obtained from Construction A applied to binary codes and $\mathbb {Z}_{4}$ –codes. A lower bound on the size of our codes for the Manhattan distance are obtained through generalized theta series of the corresponding lattices. For any fixed number of deletions, provided the number of runs is large enough our method supplies a correction technique. For fixed number of runs and binary sequence length large our lattice construction is shown to be tight up to constants.

EFFICIENT COMPRESSION OF BINARIZED TAINTED DOCUMENTS

Tainted documents are degraded or ruined documents of low quality and of worn out look. The taintations are like disparity variation, smear, ooze, uneven illumination. To enhance the visual quality of the tainted document binarization technique is applicable. Binarization can binarize all the tainted documents but performing binarization to faultily tainted documents is a complicated task, the complication is observed in the identification of variations between the document background and text foreground. The system uses OTSU binarization that can binarize any kind of taintations. The proposed technique addresses the variations between background and foreground text of the document and calculates the optimum threshold separating the two classes so that their combined spread is minimal or equivalent hence the vision quality increases. Enhancement of vision quality also results in the enhancement of document size. Compression is performed on the binarized tainted document to reduce the tainted document size. The compression technique projected to use in this paper is Run Length coding which helps to reduce the size of the tainted document. Run Length coding is lossless compression technique which is very successful in dealing with binary images.

RETRACTED ARTICLE: Augmented Recurrence Hopping Based Run-Length Coding for Test Data Compression Applications

The advancement in technologies has been increasing with increase in integrating scales which allows fabricating millions of transistors on a chip. This demands the efficient testing circuit to evaluate the fault present, where the large volume of data volume needs to be tested during manufacturing and fabrication. Therefore, the challenging fact arises in methodologies to achieve the test data compression. Even though various techniques in the present scenario reduce the testing time, improvement in data volume reduction is still a demanding factor. The proposed scheme aims to obtain a Large Compression Ratio. By using Augmented Recurrence Hopping based Run-Length Coding (ARHRLC) Test Data volume can be reduced and data can be compressed. The proposed ARHRLC coding technique which compares the group code based test vector and it’s duplicate. Data sequence can be decreased in terms volume and area overhead. From the analysis of ISCAS 89 benchmark circuit’s performance shows the proposed coding scheme outperforms the conventional test data compression methods. The Augmented Recurrence Hopping based Run-Length Coding procedure skips the repeated sequence in the test vector group and estimate conversely perfect example of a separate test information section or various test information fragment. The test result demonstrates that the compression proportion and calculation time is lessened.

A New Steganography Technique using JPEG Images

Steganography is a form of security technique that using ambiguity to hide a secret message within an ordinary message between senders and receivers. In this paper, we propose a new steganography technique for hiding data in Joint Photo-graphic Experts Group (JPEG) images as it is the most known type of image compression between the lossy type compressions. Our proposed work is based on lossy compression (frequency domain) in images. This type of compression is susceptible to change even for the smallest amount of change which raises a difficulty to find a proper location to embed data. This should be done without affecting the image quality and without allowing anyone to notice the hidden message. From the senders side, first, we divide the image into 8*8 blocks, then apply a Discrete Cosine Transform (DCT), Quantization, and zigzag processes respectively. Second, the secret message is embedded at the end of each selected zigzag block array using the best method of our experimental results. Third, the rest of the code applies the Run Length Code (RLC), Different Pulse Code Modularity (DPCM) and Huffman encoder to obtain the compressed image that includes the embedded message. From the receiver’s side, we will reverse the previous steps to extract the secret message using an encrypted shared key via a secure channel. Our experimental results show that the best array content size of zigzag computed coefficients are between 1 to 20. This selection allows us to utilize more than half of the image blocks to embed the secret message and the difference between the cover image that holds the secret message and the original cover image is very minimal and hard to detect.

Research on battery data compression method for electric vehicles

The transmission and storage of electric vehicle battery management system (BMS) data are time consuming and infeasible, which reduces the efficiency of data transmission and storage. For this problem, this paper presents a method of battery data compression, the pre-compression is to reduce the amount of data and improve the data redundancy and repeatability, and a strategy was formulated that two universal compression methods, Huffman coding and run-length coding, were applied to different battery data. Experimental results show the method of battery data compression can obtain a good compressibility. The battery data compressibility of this paper was about 21%.

Research on battery data compression method for electric vehicles

The transmission and storage of electric vehicle battery management system (BMS) data are time consuming and infeasible, which reduces the efficiency of data transmission and storage. For this problem, this paper presents a method of battery data compression, the pre-compression is to reduce the amount of data and improve the data redundancy and repeatability, and a strategy was formulated that two universal compression methods, Huffman coding and run-length coding, were applied to different battery data. Experimental results show the method of battery data compression can obtain a good compressibility. The battery data compressibility of this paper was about 21%.

Run-Length Coding Algorithm Based Satellite Image Compression

Image compression is an application based on data compression of the digital images. Its main objective is to reduce the redundancy of the image data for storing and transmitting data in an easy way. In this system we are proposing a compression technique based on the Run-length coding algorithm based on satellite image compression. The Run-length coding algorithm is a part of the Lossless compression algorithm. The performance evolution can be done by calculating the PSNR values of the compressed images.

Run-Length Coding Algorithm Based Satellite Image Compression

Image compression is an application based on data compression of the digital images. Its main objective is to reduce the redundancy of the image data for storing and transmitting data in an easy way. In this system we are proposing a compression technique based on the Run-length coding algorithm based on satellite image compression. The Run-length coding algorithm is a part of the Lossless compression algorithm. The performance evolution can be done by calculating the PSNR values of the compressed images.

Visible watermark removal scheme based on reversible data hiding and image inpainting

In this paper, we propose two schemes for visible-watermark removal and reversible image recovery. In the first scheme, we consider the scenario for the image generated by a specific visible (not completely reversible) watermarking algorithm Chen et al. (2017). A run-length coding based method is utilized to compress the difference between the preliminary recovered image and original image. After embedding the difference information invisibly and reversibly, the final embedded image can be exactly recovered to its original version after visible-watermark removal, which avoids the problem of overflow and underflow in Chen et al. (2017). In the second scheme, the scenario of visible-watermark removal for the image generated by any visible watermarking algorithms (no matter the sender and the receiver know the algorithms or not) is considered. The scheme can perfectly remove the embedded visible watermark and can also exactly recover original image with the assist of image inpainting technique. In addition, for both two proposed schemes, the invalid user without the knowledge of secret key cannot achieve reversible recovery for original image. Experimental results demonstrate the effectiveness and superiority of our schemes.

Biased Run-Length Coding of Bilevel Classification Label Maps of Hyperspectral Images

For efficient coding of bilevel sources with some dominant symbols often found in classification label maps of hyperspectral images, we proposed a novel biased run-length (BRL) coding method, which codes the most probable symbols separately from other symbols. To determine the conditions in which the BRL coding method would be effective, we conducted an analysis of the method using statistical models. We first analyzed the effect of 2-D blocking of pixels, which were assumed to have generalized Gaussian distributions. The analysis showed that the resulting symbol blocks tended to have lower entropies than the original source without symbol blocking. We then analyzed the BRL coding method applied on the sequence of block symbols characterized by a first-order Markov model. Information-theoretic analysis showed that the BRL coding method tended to generate codewords that have lower entropies than the conventional run-length coding method. Furthermore, numerical simulations on lossless compression of actual data showed improvement of the state of the art. Specifically, end-to-end implementation integrating symbol blocking, BRL, and Huffman coding achieved up to 4.3% higher compression than the JBIG2 standard method and up to 3.2% higher compression than the conventional run-length coding method on classification label maps of the widely used “Indian Pines” dataset.

A hardware-efficient parallel architecture for real-time blob analysis based on run-length code

Blob analysis has been extensively used in target detection, object recognition, moving target tracking, among other applications. Because blob analysis is computationally expensive, it has become a bottleneck of real-time applications. To tackle this problem, a parallel algorithm for blob analysis is proposed, and a hardware-efficient architecture for this algorithm is presented in this paper. First, based on image data partition and multi-process units, a novel parallel algorithm of blob analysis is proposed to process objects with different types and sizes. Second, a dynamic convex hull calculation method is designed, which is highly efficient for parallel processing and sub-block merging of connected component labeling. Third, a parallel hardware structure of the proposed algorithm is designed and implemented on FPGA. To evaluate performance, blobs of different types and sizes are located by the proposed algorithm in software and hardware. The experimental results demonstrate that the blobs are effectively and correctly located by the proposed algorithm, and the proposed hardware architecture works more efficiently than the state-of-the-art methods.

Recognition of Music Scores with Non-Linear Distortions in Mobile Devices

Optical music recognition (OMR), when the input music score is captured by a handheld or a mobile phone camera, suffers from severe degradation in the image quality and distortions caused by non-planar document curvature and perspective projection. Hence the binarization of the input often fails to preserve the details of the original music score, leading to a poor performance in recognition of music symbols. This paper addresses the issue of staff line detection, which is the most important step in OMR, in the presence of nonlinear distortions and describes how to cope with severe degradations in recognition of music symbols. First, a RANSAC-based detection of curved staff lines is presented and staves are segmented into sub-areas for the rectification with bi-quadratic transformation. Then, run length coding is used to recognize music symbols such as stem, note head, flag, and beam. The proposed system is implemented on smart phones, and it shows promising results with music score images captured in the mobile environment.

Comparative Study on Lossless Data Compression Techniques

Image compression is a technique which removes the extraneous or unrelated information. For compression and decompression, a number of techniques such as Shannon Fano Technique, Lempel Ziv Welch, Run length Coding technique, Huffman technique etc. have been applied. In this paper, the different lossless image compression techniques have been studied. Further, a Comparative study on various techniques has been carried out and found that Embedded Zero tree Wavelet (EZW) and Set Partition in Hierarchical Transform (SPIHT) techniques perform better in terms of Compression Ratio (CR), Peak Signal To Noise Ratio (PSNR) and Mean Square Error (MSE)

An Efficient Compound Image Compression Using Optimal Discrete Wavelet Transform and Run Length Encoding Techniques

Abstract Reduction in file size leads to reduction in the number of bits required to store it. When data is compressed, it must be decompressed into its original form bit for bit. Compound images are defined as images that contain a combination of text, natural (photo) images and graphic images. Here, compression is the process of reducing the amount of data required to represent information. Image compression is done on the basis of various loss and lossless compression algorithms. This research work deals with the preprocessing and transformations used to compress a compound image to produce a high compression ratio (CR), less compression time and so on. In the compression process the images are considered for preprocessing and discrete wavelet transform with adaptive particle swarm optimization process. The purpose of this optimization technique is to optimize the wavelet coefficient in Harr wavelet for improving the CR value. In the image compression process, run length coding is used to compress the compound images. Based on this technique, it produces minimum CR and less computation time of compound images.

Joint image encryption and compression scheme based on a new hyperchaotic system and curvelet transform

This paper proposes a joint image encryption and compression scheme based on a new hyperchaotic system and curvelet transform. A new five-dimensional hyperchaotic system based on the Rabinovich system is presented. By means of the proposed hyperchaotic system, a new pseudorandom key stream generator is constructed. The algorithm adopts diffusion and confusion structure to perform encryption, which is based on the key stream generator and the proposed hyperchaotic system. The key sequence used for image encryption is relation to plain text. By means of the second generation curvelet transform, run-length coding, and Huffman coding, the image data are compressed. The joint operation of compression and encryption in a single process is performed. The security test results indicate the proposed methods have high security and good compression effect.

ECG compression based on combining of EMD and wavelet transform

A new electrocardiogram (ECG) compression method based on the combination of the empirical mode decomposition (EMD) and the wavelet transform is presented. ECG signal can be decomposed into a set of intrinsic mode functions by the EMD. The proposed method recomposes the intrinsic mode functions into two groups, and compresses each group separately to fully utilise their data characteristics. The first group can be completely described by its extrema with negligible reconstruction error, while the second group is further decomposed by wavelet transform. With appropriate threshold selecting and the using of the run length coding and the Huffman coding, the proposed method exhibits competitive performances compared with other compressors for ECG compression.

Compression of Data using Shifted Frequency Directed Reference Coding and MISR

In modern technology BIST become pervasive where scan chain plays a major role. An efficient low power BIST method is proposed which occurs in testing. The test set acquires sequence of preprocessed approach inclusive of X-bit 2-D reordering and cube matrix is sequentially distributed. In this paper compression ratio is achieved using MISR. The introduction of MISR and X-masking technique will reduce the compression Ratio. To minimise the repitation of bits MISR plays a vital role. Compression is done by the run length coding and the high compression is achived by the first and second matrix response. MT flling is a method for the replacement technique.CR is calculated using the output values used. The ratio of input bits used to the existing input values which shows the compression ratio. This proposed technique is compared with bench mark circuits s5378, s9234 and s13207 to analyze the area and compression ratio.

Implementation of Separable Reversible Data Hiding Scheme in Image Encryption Process

Background/Objectives: Image encryption includes a vital role within the field of cryptography. Within the planned theme compression technique is introduced when the encryption and information concealment method to cut back the image size for quicker transmission. Methods/Statistical Analysis: Encryption scheme, 2 individual keys are used for image cryptography & information concealment with high level of security to safeguard a picture from unauthorized access. The owner of the content encrypts the first image that is not compressed by using a cryptography key. The LSBs of the image encrypted are compressed employing an information concealment key to form an area to imbed an extra information. Haar wavelet compression technique and Run - Length coding (RLC) were used. Findings: At the receiver end, the quality of the image retrieved and the information extracted are achieved solely from Run–Length Coding with their several keys. Extracted image quality is analyzed by standard and subjective metrics index are measured. Application/Improvements: Image Quality Assessment (IQA) technique shows the standard of retrieved image is same as that of the first image.

A Review of Image Compression Techniques

An image compression method eradicates redundant and/or unrelated information, and resourcefully encodes leftovers. Practically, it is frequently essential to toss away both non redundant information and relevant information to attain the essential compression. In any case, the ploy is discovering methods that permit important information to be resourcefully extracted and represented. This paper copes with dissimilar compression methods for comprising the information in an image. The information can be compressed by means of Lossy techniques such as Quantization, Transform coding, Block Transform Coding or Lossless techniques such as Run Length Coding, Lossless Predictive Coding, Multi-resolution Coding. All these techniques have been discussed in this paper and the performance of any technique/method is analyzed on various parameters like MSE and PSNR.