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Journal articles on the topic 'Linde-Buzo-Gray (LBG)'

Author: Grafiati

Published: 3 June 2025

Last updated: 19 July 2025

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1

Severo, Verusca, Felipe B. S. Ferreira, Rodrigo Spencer, Arthur Nascimento, and Francisco Madeiro. "On the Initialization of Swarm Intelligence Algorithms for Vector Quantization Codebook Design." Sensors 24, no. 8 (2024): 2606. http://dx.doi.org/10.3390/s24082606.

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Vector Quantization (VQ) is a technique with a wide range of applications. For example, it can be used for image compression. The codebook design for VQ has great significance in the quality of the quantized signals and can benefit from the use of swarm intelligence. Initialization of the Linde–Buzo–Gray (LBG) algorithm, which is the most popular VQ codebook design algorithm, is a step that directly influences VQ performance, as the convergence speed and codebook quality depend on the initial codebook. A widely used initialization alternative is random initialization, in which the initial set

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2

G, Venu. "Codebook Optimization Using ACO Algorithm." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31753.

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The ACO algorithm, inspired by ant behavior, is used to optimize codebooks in speech processing. This study focuses on compressing speech signals efficiently to reduce bandwidth usage. Vector Quantization, a block coding technique, is employed, utilizing codebooks generated by the Linde-Buzo-Gray (LBG) algorithm. The ACO algorithm is proposed as an optimization method for these codebooks, aiming to minimize spectral distortion. Results show that ACO-optimized codebooks reduce spectral distortion. Keywords— Vector quantization, Speech compression, Linde-Buzo-Gray, ACO.

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3

Bakshi, Aditya, Akhil Gupta, Sudeep Tanwar, et al. "Performance Augmentation of Cuckoo Search Optimization Technique Using Vector Quantization in Image Compression." Mathematics 11, no. 10 (2023): 2364. http://dx.doi.org/10.3390/math11102364.

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For constructing the best local codebook for image compression, there are many Vector Quantization (VQ) procedures, but the simplest VQ procedure is the Linde–Buzo–Gray (LBG) procedure. Techniques such as the Gaussian Dissemination Function (GDF) are used for the searching process in generating a global codebook for particle swarm optimization (PSO), Honeybee mating optimization (HBMO), and Firefly (FA) procedures. However, when particle velocity is very high, FA encounters a problem when brighter fireflies are trivial, and PSO suffers uncertainty in merging. A novel procedure, Cuckoo Search–K

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Bilal, Muhammmad, Zahid Ullah, Omer Mujahid, and Tama Fouzder. "Fast Linde–Buzo–Gray (FLBG) Algorithm for Image Compression through Rescaling Using Bilinear Interpolation." Journal of Imaging 10, no. 5 (2024): 124. http://dx.doi.org/10.3390/jimaging10050124.

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Vector quantization (VQ) is a block coding method that is famous for its high compression ratio and simple encoder and decoder implementation. Linde–Buzo–Gray (LBG) is a renowned technique for VQ that uses a clustering-based approach for finding the optimum codebook. Numerous algorithms, such as Particle Swarm Optimization (PSO), the Cuckoo search algorithm (CS), bat algorithm, and firefly algorithm (FA), are used for codebook design. These algorithms are primarily focused on improving the image quality in terms of the PSNR and SSIM but use exhaustive searching to find the optimum codebook, wh

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5

Schulz, Christoph, Kin Chung Kwan, Michael Becher, et al. "Multi-class inverted stippling." ACM Transactions on Graphics 40, no. 6 (2021): 1–12. http://dx.doi.org/10.1145/3478513.3480534.

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We introduce inverted stippling , a method to mimic an inversion technique used by artists when performing stippling. To this end, we extend Linde-Buzo-Gray (LBG) stippling to multi-class LBG (MLBG) stippling with multiple layers. MLBG stippling couples the layers stochastically to optimize for per-layer and overall blue-noise properties. We propose a stipple-based filling method to generate solid color backgrounds for inverting areas. Our experiments demonstrate the effectiveness of MLBG in terms of reducing overlapping and intensity accuracy. In addition, we showcase MLBG with color stipplin

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6

Tsai, Piyu, Yu-Chen Hu, and Hsiu-Lien Yeh. "Fast VQ Codebook Generation Method Using Codeword Stability Check and Finite State Concept." Fundamenta Informaticae 87, no. 3-4 (2008): 447–63. https://doi.org/10.3233/fun-2008-873-409.

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The codebook design in the vector quantization scheme is important because it affects the image quality of the encoded image. The Linde-Buzo-Gray (LBG) codebook generation algorithm is well known and a popular choice among codebook users. However, a heavy computational complexity is consumed for the iteratively clustering process in the LBG algorithm. In this paper, the similarity of codewords in consecutive rounds of the LBG algorithm is exploited to reduce the computational complexity. By checking the stability of codewords, the status of each codeword in the codebook can be determined. Only

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Chiranjeevi, Karri, Umaranjan Jena, and Sonali Dash. "Comparative Performance Analysis of Optimization Techniques on Vector Quantization for Image Compression." International Journal of Computer Vision and Image Processing 7, no. 1 (2017): 19–43. http://dx.doi.org/10.4018/ijcvip.2017010102.

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Linde-Buzo-Gray (LBG) Vector Quantization (VQ), technically generates local codebook after many runs on different sets of training images for image compression. The key role of VQ is to generate global codebook. In this paper, we present comparative performance analysis of different optimization techniques. Firefly and Cuckoo search generate a near global codebook, but undergoes problem when non-availability of brighter fireflies and convergence time is very high respectively. Hybrid Cuckoo Search (HCS) algorithm was developed and tested on four benchmark functions, that optimizes the LBG code

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MADEIRO, F., R. M. VILAR, J. M. FECHINE, and B. G. AGUIAR NETO. "A Self-Organizing Algorithm for Vector Quantizer Design Applied to Signal Processing." International Journal of Neural Systems 09, no. 03 (1999): 219–26. http://dx.doi.org/10.1142/s0129065799000216.

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Vector quantization plays an important role in many signal processing problems, such as speech/speaker recognition and signal compression. This paper presents an unsupervised algorithm for vector quantizer design. Although the proposed method is inspired in Kohonen learning, it does not incorporate the classical definition of topological neighborhood as an array of nodes. Simulations are carried out to compare the performance of the proposed algorithm, named SOA (self-organizing algorithm), to that of the traditional LBG (Linde-Buzo-Gray) algorithm. The authors present an evaluation concerning

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Hakim, Faruq Abdul, Tio Dharmawan, and Muhamad Arief Hidayat. "Gender classification performance optimization based on facial images using LBG-VQ and MB-LBP." International Journal of Advances in Intelligent Informatics 11, no. 1 (2025): 72. https://doi.org/10.26555/ijain.v11i1.1827.

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In the computer vision and machine learning field, especially for gender classification based on facial images, feature extraction is one of the inseparable parts. Various features can be extracted from images, including texture features. Several prior studies show that the Linde Buzo gray vector quantization (LBG-VQ) and Multi-block local binary pattern (MB-LBP) methods can extract texture features from images. The LBG-VQ produces less optimal performance in gender classification on the FEI facial images dataset. On the other hand, the MB-LBP produces more optimal performance when applied to

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10

A. Alkhaldi, Nora, Rawabi Abdulaziz Abdullah Alsedais, Hanan T. Halawani, and Sayed M. Abdelkhalek Aboutaleb. "Manta Ray Foraging Optimization with Vector Quantization Based Microarray Image Compression Technique." Computational Intelligence and Neuroscience 2022 (May 25, 2022): 1–13. http://dx.doi.org/10.1155/2022/7140552.

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DNA microarray technologies enable the analysis of the expression of numerous genes in an individual experiment and become an important approach in the field of medicine and biology for investing genetic function, regulation, and interaction. Microarray images can be investigated well for obtaining the contained genetic data. But is it undesirable to retain the genetic data and avoid the microarray images? Due to considerable attention to DNA microarray and several experiments being performed under distinct conditions, a massive quantity of data gets produced over the globe. In order to store

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11

Zaw, Win Aung. "A Robust Speaker Identification System." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 2057–64. https://doi.org/10.31142/ijtsrd18274.

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This paper is aimed to implement a robust speaker identification system. It is a software architecture which identifies the current talker out of a set of speakers. The system is emphasized on text dependent speaker identification system. It contains three main modules endpoint detection, feature extraction and feature matching. The additional module, endpoint detection, removes unwanted signal and background noise from the input speech signal before subsequent processing. In the proposed system, Short Term Energy analysis is used for endpoint detection. Mel frequency Cepstrum Coefficients MFC

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12

Suman, M., Habibulla Khan, M.Madhavi Latha, and D.Aruna Kumari. "Enhancement of Compressed Speech Signal using Recursive Filter." COMPUSOFT: An International Journal of Advanced Computer Technology 02, no. 08 (2013): 261–66. https://doi.org/10.5281/zenodo.14613331.

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Speech compression, enhancement and recognition in noisy, reverberant conditions is a challenging task. In this paper a new approach to this problem, which is developed in the framework of probabilistic random modeling. speech coding techniques are commonly used in low bit rate analysis and synthesis . Coding algorithms seek to minimize the bit rate in the digital representation of a signal without an objectionable loss of signal quality in the process. As the compression techniques that are used are Lossy compression technique and there is every possibility of loss in quality. Speech enhancem

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13

Lee, Won-Seok, and Hyoung-Kyu Song. "Efficient Channel Feedback Scheme for Multi-User MIMO Hybrid Beamforming Systems." Sensors 21, no. 16 (2021): 5298. http://dx.doi.org/10.3390/s21165298.

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This paper proposes an efficient channel information feedback scheme to reduce the feedback overhead of multi-user multiple-input multiple-output (MU-MIMO) hybrid beamforming systems. As massive machine type communication (mMTC) was considered in the deployments of 5G, a transmitter of the hybrid beamforming system should communicate with multiple devices at the same time. To communicate with multiple devices in the same time and frequency slot, high-dimensional channel information should be used to control interferences between the receivers. Therefore, the feedback overhead for the channels

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14

Arup, Kumar Pal, and Sar Anup. "AN EFFICIENT CODEBOOK INITIALIZATION APPROACH FOR LBG ALGORITHM." August 31, 2011. https://doi.org/10.5281/zenodo.1232984.

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In VQ based image compression technique has three major steps namely (i) Codebook Design, (ii) VQ Encoding Process and (iii) VQ Decoding Process. The performance of VQ based image compression technique depends upon the constructed codebook. A widely used technique for VQ codebook design is the Linde-Buzo-Gray (LBG) algorithm. However the performance of the standard LBG algorithm is highly dependent on the choice of the initial codebook. In this paper, we have proposed a simple and very effective approach for codebook initialization for LBG algorithm. The simulation results show that the propos

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15

Satish Kumar, T., S. Jothilakshmi, Batholomew C. James, M. Prakash, N. Arulkumar, and C. Rekha. "HHO-Based Vector Quantization Technique for Biomedical Image Compression in Cloud Computing." International Journal of Image and Graphics, December 31, 2021. http://dx.doi.org/10.1142/s0219467822400083.

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In the present digital era, the exploitation of medical technologies and massive generation of medical data using different imaging modalities, adequate storage, management, and transmission of biomedical images necessitate image compression techniques. Vector quantization (VQ) is an effective image compression approach, and the widely employed VQ technique is Linde–Buzo–Gray (LBG), which generates local optimum codebooks for image compression. The codebook construction is treated as an optimization issue solved with utilization of metaheuristic optimization techniques. In this view, this pape

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16

M., Lakshmi, and Senthil Kumar J. "Optimized Vector Quantization for Bayer Color Filter Array." October 1, 2015. https://doi.org/10.5281/zenodo.1109806.

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Digital cameras to reduce cost, use an image sensor to capture color images. Color Filter Array (CFA) in digital cameras permits only one of the three primary (red-green-blue) colors to be sensed in a pixel and interpolates the two missing components through a method named demosaicking. Captured data is interpolated into a full color image and compressed in applications. Color interpolation before compression leads to data redundancy. This paper proposes a new Vector Quantization (VQ) technique to construct a VQ codebook with Differential Evolution (DE) Algorithm. The new technique is compared

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17

Al-Salamee, Baidaa A., and Dhiah Al-Shammary. "Semi-lossless Fractal MRI Image Compression Based on Fixed length Technique." Journal of Al-Qadisiyah for Computer Science and Mathematics 13, no. 3 (2021). http://dx.doi.org/10.29304/jqcm.2021.13.3.854.

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Medical image compression plays an essential role to handle large amounts of data for communication and storage purposes. Fractal image compression is a potential lossy compression models with a resulting image that loses some of its information. However, health data communication usually cannot afford any lose for patients visual information. This paper proposes a new high efficiency semi-lossless fractal image compression method (SLFIC) based on fractal theory and fixed length technique. Technically, the resultant lossy fractals compressed image is analyzed and error in comparison with the o

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18

Aung, Zaw Win. "Speech to Text Conversion System for Myanmar Alphabet." International Journal of Science and Engineering Applications, April 12, 2023, 175–76. http://dx.doi.org/10.7753/ijsea0708.1009.

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This paper is aimed to implement the speech to text conversion system for Myanmar alphabet. The Myanmar alphabet consists of 33 characters from ?ka? to ?ah?. The proposed system is software architecture which allows the user to speak against the computer in Myanmar language and the corresponding character is printed on the screen in the Microsoft Office Word Document Format. The system is emphasized on Speaker Independent Isolated Word Recognition System. The proposed system directly acquires and converts speech to text. This system contains two main modules: feature extraction and feature mat

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19

Mankovich, Nathan, Helene Andrews-Polymenis, David Threadgill, and Michael Kirby. "Module representatives for refining gene co-expression modules." Physical Biology, April 19, 2023. http://dx.doi.org/10.1088/1478-3975/acce8d.

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Abstract This paper concerns the identification of gene co-expression modules in transcriptomics data, i.e., collections of genes which are highly co-expressed and potentially linked to a biological mechanism. WGCNA (Weighted Gene Co-expression Network Analysis) is a widely used method for module detection based on the computation of eigengenes, the weights of the first principal component for the module gene expression matrix. This eigengene has been used as a centroid in a $k$-means algorithm to improve module memberships. In this paper, we present four new module representatives: the eigeng

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20

"Image Compression Using Different Vector Quantization Algorithms and Its Comparison." International Journal of Innovative Technology and Exploring Engineering 8, no. 9 (2019): 3459–88. http://dx.doi.org/10.35940/ijitee.i8165.078919.

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Image compression techniques are presented in this paper which can be used for storage and transmission of digital lossy images. It is mostly important in both multimedia and medical field to store huge database and data transfer. Medical images are used for diagnosis purposes. So, vector quantization is a novel method for lossy image compression that includes codebook design, encoding and decoding stages. Here, we have applied different lossy compression techniques like VQ-LBG (Vector quantization- Linde, Buzo and Gray algorithm), DWT-MSVQ (Discrete wavelet transform-Multistage Vector quantiz

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Cheima, Ben Soltane, and Yonas Kelbesa Ittansa. "An Intelligent Text Independent Speaker Identification Using VQ-GMM Model Based Multiple Classifier System." August 4, 2015. https://doi.org/10.5281/zenodo.1108442.

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvemen

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