Binary Vector Quantization Research Articles

Pengenalan Finger Vein Menggunakan Local Line Binary Pattern dan Learning Vector Quantization

This research proposes finger vein recognition system using Local Line Binary Pattern (LLBP) method and Learning Vector Quantization (LVQ). LLBP is is the advanced feature extraction method of Local Binary Pattern (LBP) method that uses a combination of binary values from neighborhood pixels to form features of an image. The straight-line shape of LLBP can extract robust features from the images with unclear veins, it is more suitable to capture the pattern of vein in finger vein image. At the recognition stage, LVQ is used as a classification method to improve recognition accuracy, which has been shown in earlier studies to show better results than other classifier methods. The three main stages in this research are preprocessing, feature extraction using LLBP method and recognition using LVQ. The proposed methodology has been tested on the SDUMLA-HMT finger vein image database from Shandong University. The experiment shows that the proposed methodology can achieve accuracy up to 90%.
 Index Terms—finger vein recognition, Learning Vector Quantization, LLBP, Local Line Binary Pattern, LVQ.

Identification of multifunctional cytotoxic T-cell subsets as immune correlates with clinical outcomes in a phase II study of AGS-003, an autologous dendritic cell-based therapy administered to patients with newly diagnosed, metastatic RCC.

80 Background: AGS-003 is an autologous dendritic cell (DC) immunotherapy prepared from matured monocyte-derived DC co-electroporated with the subject’s own amplified tumor RNA and synthetic CD40L RNA. The mechanism of action (MOA) of AGS-003 was evaluated in combination with sunitinib for treatment of advanced renal cell carcinoma (RCC) in AGS-003-006, an open label phase II trial including subjects with newly diagnosed, unfavorable-risk, metastatic clear cell RCC. The goal of the immune monitoring platform is to identify unique cytotoxic T-cell (CTL) signatures that correlate with clinical outcome in subjects receiving AGS-003 in combination with sunitinib. Methods: Multiparametric flow cytometry was used to identify tumor-reactive CTL subsets induced by AGS-003 based on combinatorial expression patterns of surface markers CD28, CD45RA, CD27 and CCR7. Moreover, further partitioning of each CTL subset identified combinatorial expression patterns of Markers of Immune Function (MIFs) defined as cytokines (IFN-γ TNF-α, IL-2), cytolytic markers (Granzyme b, CD107) and proliferation. Correlates of CTL signatures with clinical outcome were analyzed using an adaptation of a binary tree-structured vector quantization (BTSVQ) approach, originally developed to cluster and visualize large microarray data sets. The BTSVQ approach implements a two-way unsupervised clustering that allows a subject’s CTL signature to be mapped based on both surface marker and MIFs expression patterns to identify unique clustering patterns linked to clinical outcome. Results: Data analysis identified a unique CTL signature (CD28+/CCR7+/CD45RA- phenotype) displaying a broad MIFs profile as a statistically significant correlate to PFS and OS in patients treated with AGS-003. Conclusions: These results support the intended MOA of AGS-003 in vivo, as the induction of anti-tumor central and effector memory CTL responses. These data warrant further immunological evaluation of AGS-003 in the randomized phase III ADAPT study using AGS-003 in combination with standard treatment in RCC subjects.

Sex-specific differences in placental global gene expression in pregnancies complicated by asthma

BackgroundChronic maternal asthma is associated with reduced growth of the female fetus and normal growth of the male fetus. The mechanisms that control the differential effects of maternal asthma on the fetus have not been fully elucidated but alterations in placental function may play a role. In the current study we have used microarray platform to examine fetal sex-specific global changes in placental gene expression in pregnancies complicated by asthma as compared to non-asthmatic subjects. MethodsPlacental RNA was extracted from 11 control subjects and 38 asthmatic subjects. Labeled cDNA was hybridized to an oligonucleotide chip with 1700 double spotted well-characterized human genes. Global gene expression data analysis and visualization were performed using the Binary Tree-Structured Vector Quantization (BTSVQ) software. Functional relationships of differentially expressed genes were assessed using protein–protein interaction database I2D, network analysis and visualization software NAViGaTOR and Ingenuity Pathway Analysis software. ResultsOverall, 65 genes were found to be altered in placentae of pregnancies complicated by asthma. Of these, only 6 genes were altered in male placentae. There were 59 gene changes in female placentae of asthmatic mothers relative to control placentae. Some of the sex-specific genes were associated with growth, inflammation and immune pathways. ConclusionThere are sex-specific alterations in placental gene expression in the presence of maternal asthma. Given that many of the identified genes in the female placentae were associated with or involved in cellular growth and tissue development, these may contribute to the sexually dimorphic difference in fetal growth in response to maternal asthma.

Molecular Evidence of Placental Hypoxia in Preeclampsia

Oxygen plays a central role in human placental pathologies including preeclampsia, a leading cause of fetal and maternal death and morbidity. Insufficient uteroplacental oxygenation in preeclampsia is believed to be responsible for the molecular events leading to the clinical manifestations of this disease. Using high-throughput functional genomics, we determined the global gene expression profiles of placentae from high altitude pregnancies, a natural in vivo model of chronic hypoxia, as well as that of first-trimester explants under 3 and 20% oxygen, an in vitro organ culture model. We next compared the genomic profile from these two models with that obtained from pregnancies complicated by preeclampsia. Microarray data were analyzed using the binary tree-structured vector quantization algorithm, which generates global gene expression maps. Our results highlight a striking global gene expression similarity between 3% O(2)-treated explants, high-altitude placentae, and importantly placentae from preeclamptic pregnancies. We demonstrate herein the utility of explant culture and high-altitude placenta as biologically relevant and powerful models for studying the oxygen-mediated events in preeclampsia. Our results provide molecular evidence that aberrant global placental gene expression changes in preeclampsia may be due to reduced oxygenation and that these events can successfully be mimicked by in vivo and in vitro models of placental hypoxia.

The Improved Binary Tree Vector Quantization Using Spatial Sensitivity of HVS

In this paper, we proposed an improved binary tree vector quantization in special consideration of the area of spatial sensitivity which is an important characteristic of the human visual system. We regarded spatial sensitivity as a function of the human visual system, which works using variations of the three primary colors in blocks of input images. In addition, we applied the weight derived from HVS spatial sensitivity to the process of splitting nodes using eigenvectors in binary tree vector quantization. The test results showed that the proposed method provided better visual quality and greater PSNR than conventional methods.

인간 시각 시스템의 공간 지각 특성을 이용한 개선된 이진트리 벡터양자화

칼라 양자화는 칼라 카메라로부터 입력된 자연 색의 칼라 영상을 컴퓨터 모니터에 표현하기 위해 더 적은 칼라 팔레트로 구성하는 것이다. 이것은 자연색 중에서 인간이 인식한 수 있는 색은 수 백가지 정도일 뿐 아니라 실제 칼라 영상에 나타나는 색은 이 보다는 훨씬 적다는 것을 바탕으로 한다. 본 논문에서는 인간의 시각 특성중 공간 지각 특성을 고려한 개선된 고유벡터를 이용한 이진 트리 벡터양자화 기법을 제안한다. 제안 방법은 고유벡터를 이용한 이진 트리 벡터 양자화의 두 노드로 분할하는 과정에 영상의 블록 내의 칼라의 변화에 따른 인간의 시각의 반응 정도를 가중피로 결합하여 양자화를 하였다. 제안 방법은 기존의 방법보다 색상이 선명해지며 유사한 영역의 분한에 뛰어난 성능을 보여 주었으며 주관적인 화질 평가와 PSNR에서도 좋은 결과를 보였다. Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. The basic problem is how to display 256 colors or less colors, called color palette, In this paper, we propose improved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on the responsibility of human visual system according to changes of three Primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective quality test and WSNR.

Performance of quantizers on noisy channels using structured families of codes

Achievable distortion bounds are derived for the cascade of structured families of binary linear channel codes and binary lattice vector quantizers. It is known that for the cascade of asymptotically good channel codes and asymptotically good vector quantizers the end-to-end distortion decays to zero exponentially fast as a function of the overall transmission rate, and is achieved by choosing a channel code rate that is independent of the overall transmission rate. We show that for certain families of practical channel codes and binary lattice vector quantizers, the overall distortion can be made to decay to zero exponentially fast as a function of the square root of transmission rate. This is achieved by carefully choosing a channel code rate that decays to zero as the transmission rate grows. Explicit channel code rate schedules are obtained for several well-known families of channel codes.

Binary vector quantizer design using soft centroids

Soft centroids method is proposed for binary vector quantizer design. Instead of using binary centroids, the codevectors can take any real value between one and zero during the codebook generation process. The binarization is performed only for the final codebook. The proposed method is successfully applied for three existing codebook generation algorithms: GLA, SA and PNN.

Binary lattice vector quantization with linear block codes and affine index assignments

We determine analytic expressions for the performance of some low-complexity combined source-channel coding systems. The main tool used is the Hadamard transform. In particular, we obtain formulas for the average distortion of binary lattice vector quantization with affine index assignments, linear block channel coding, and a binary-symmetric channel. The distortion formulas are specialized to nonredundant channel codes for a binary-symmetric channel, and then extended to affine index assignments on a binary-asymmetric channel. Various structured index assignments are compared. Our analytic formulas provide a computationally efficient method for determining the performance of various coding schemes. One interesting result shown is that for a uniform source and uniform quantizer, the natural binary code is never optimal for a nonsymmetric channel, even though it is known to be optimal for a symmetric channel.

Recursive partitioning to reduce distortion

Adaptive partitioning of a multidimensional feature space plays a fundamental role in the design of data-compression schemes. Most partition-based design methods operate in an iterative fashion, seeking to reduce distortion at each stage of their operation by implementing a linear split of a selected cell. The operation and eventual outcome of such methods is easily described in terms of binary tree-structured vector quantizers. This paper considers a class of simple growing procedures for tree-structured vector quantizers. Of primary interest is the asymptotic distortion of quantizers produced by the unsupervised implementation of the procedures. It is shown that application of the procedures to a convergent sequence of distributions with a suitable limit yields quantizers whose distortion tends to zero. Analogous results are established for tree-structured vector quantizers produced from stationary ergodic training data. The analysis is applicable to procedures employing both axis-parallel and oblique splitting, and a variety of distortion measures. The results of the paper apply directly to unsupervised procedures that may be efficiently implemented on a digital computer.

Optimal binary vector quantization via enumeration of covering codes

Binary vector quantization (BVQ) refers to block coding of binary vectors under a fidelity measure. Covering codes were studied as a means of lattice BVQ. But a further source coding problem hidden in the equivalence of covering codes has seemingly eluded attention. Given a d-dimensional hypercube (code space), equivalent covering codes of the same covering radius but of different codewords have different expected BVQ distortions for a general probability mass function. Thus one can minimize, within the code equivalence, the expected distortion over all different covering codes. This leads a two-stage optimization scheme for BVQ design. First we use an optimal covering code to minimize the maximum per-vector distortion at a given rate. Then under the minmax constraint, we minimize the expected quantization distortion. This minmax constrained BVQ method (MCBVQ) controls both the maximum and average distortions, and hence improves subjective quality of compressed binary images, MCBVQ also avoids poor local minima that may trap the generalized Lloyd method. The [7,4] Hamming code and [8,4] extended Hamming code are found to be particularly suitable for MCBVQ on binary images. An efficient and simple algorithm is introduced to enumerate all distinct [7,4] Hamming/[8,4] extended Hamming codes and compute the corresponding expected distortions in optimal MCBVQ design. Furthermore, MCBVQ using linear covering codes has a compact codebook and a fast syndrome-encoding algorithm.

Transmission of analog signals using multicarrier modulation: a combined source-channel coding approach

We have proposed and analyzed a combined source-channel coding scheme using multicarrier modulation. By changing the power and modulation of subchannels carrying different bits of the quantized signal, the channel-induced distortion can be minimized. We derive an algorithm for the allocation of power among subchannels. Analog sources quantized by scalar and vector quantizers are considered. For a Gaussian source scalar-quantized to 8 bit, multicarrier transmission yields a 13 dB improvement of signal-to-distortion ratio over a single-carrier system. Quantizers having a smaller number of bits yield smaller improvements. We consider both full-search and binary tree-search vector quantizers using a natural binary coding scheme. For a vector quantizer using 2 b/sample, multicarrier transmission yields an improvement in signal-to-distortion ratio that lies between 0.3 and 0.8 dB, depending on the quantizer design.

VLSI systolic binary tree-searched vector quantizer for image compression

A high-speed image compression VLSI processor based on the systolic architecture of difference-codebook binary tree-searched vector quantization has been developed to meet the increasing demands on large-volume data communication and storage requirements. Simulation results show that this design is applicable to many types of image data and capable of producing good reconstructed data quality at high compression ratios. Various design aspects of the binary tree-searched vector quantizer including the algorithm, architecture, and detailed functional design are thoroughly investigated for VLSI implementation. An 8-level difference-codebook binary tree-searched vector quantizer can be implemented on a custom VLSI chip that includes a systolic array of eight identical processors and a hierarchical memory of eight subcodebook memory banks. The total transistor count is about 300000 and the die size is about 8.67/spl times/7.72 mm/sup 2/ in a 1.0 /spl mu/m CMOS technology. The throughput rate of this high-speed VLSI compression system is approximately 25 Mpixels per second and its equivalent computation power is 600 million instructions per second.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Average number of facets per cell in tree-structured vector quantizer partitions

Upper and lower bounds are derived for the average number of facets per cell in the encoder partition of binary tree-structured vector quantizers. The achievability of the bounds is described as well. It is shown that the average number of facets per cell for unbalanced trees must lie asymptotically between three and four in R/sup 2/, and each of these bounds can be achieved, whereas for higher dimensions it is shown that an arbitrarily large percentage of the cells can each have a linear number (in codebook size) of facets. Analogous results are also indicated for balanced trees. >

A bit-level systolic architecture for implementing a VQ tree search

A bit-level systolic array system for performing a binary tree Vector Quantization codebook search is described. This consists of a linear chain of regular VLSI building blocks and exhibits data rates suitable for a wide range of real-time applications. A technique is described which reduces the computation required at each node in the binary tree to that of a single inner product operation. This method applies to all the common distortion measures (including the Euclidean distance, the Weighted Euclidean distance and the Itakura-Saito distortion measure) and significantly reduces the hardware required to implement the tree search system.

Block classification scheme using binary vector quantization for image coding

We present a method to partition the codebook, according to the visual perception, based upon binary vector quantization (VQ), which can be used for any kind of image. We also describe a way of reducing VQ computation at the encoder by applying an orthogonal transformation without increasing computation at the decoder.

Image coding using vector quantization: a review

A review of vector quantization techniques used for encoding digital images is presented. First, the concept of vector quantization is introduced, then its application to digital images is explained. Spatial, predictive, transform, hybrid, binary, and subband vector quantizers are reviewed. The emphasis is on the usefulness of the vector quantization when it is combined with conventional image coding techniques, or when it is used in different domains.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>