Finger-Knuckle-Print recognition performance improvement via multi-instance fusion at the score level

Fusion of multiple instances within a modality for improving the performance of biometric verification has attracted much attention in recent years. In this letter, we present an efficient Finger-Knuckle-Print (FKP) recognition algorithm based on multi-instance fusion, which combines the left index/middle and right index/middle fingers of an individual at the matching score level. Before fusing, a novel normalization strategy is applied on each score and a fused score is generated for the final decision by summing the normalized scores. The experimental results on Poly-U FKP database show that the proposed method has an obvious performance improvement compared with the single-instance method and different normalization strategies.     

Multimodal biometric authentication based on score level fusion using support vector machine

Fusion of multiple biometrics for human authentication performance improvement has received considerable attention. This paper presents a novel multimodal biometric authentication method integrating face and iris based on score level fusion. For score level fusion, support vector machine (SVM) based fusion rule is applied to combine two matching scores, respectively from Laplacianface based face verifier and phase information based iris verifier, to generate a single scalar score which is used to make the final decision. Experimental results show that the performance of the proposed method can bring obvious improvement comparing to the unimodal biometric identification methods and the previous fused face-iris methods.     

An improved fusion algorithm for infrared and visible images based on multi-scale transform

In this paper, an improved fusion algorithm for infrared and visible images based on multi-scale transform is proposed. First of all, Morphology-Hat transform is used for an infrared image and a visible image separately. Then two images were decomposed into high-frequency and low-frequency images by contourlet transform (CT). The fusion strategy of high-frequency images is based on mean gradient and the fusion strategy of low-frequency images is based on Principal Component Analysis (PCA). Finally, the final fused image is obtained by using the inverse contourlet transform (ICT). The experiments and results demonstrate that the proposed method can significantly improve image fusion performance, accomplish notable target information and high contrast and preserve rich details information at the same time.     

基于小波分解和进化策略的图像融合方法

提出了一种基于小波分解和进化策略相结合的多聚焦图像融合方法。该方法首先对不同聚焦点图像进行无下采小波分解，并分别将其各方向、各尺度的高频信息进行叠加，然后依据它们在高频信息叠加层上对应的局部区域能量的差异，采用进化策略进行区域划分，进而实现分区域融合。实验结果表明所提出的方法比小波变换法具有更好的融合效果。     

A Multi-Modal Fusion Method Based on Higher-Order Orthogonal Iteration Decomposition

Multi-modal fusion can achieve better predictions through the amalgamation of information from different modalities. To improve the performance of accuracy, a method based on Higher-order Orthogonal Iteration Decomposition and Projection (HOIDP) is proposed, in the fusion process, higher-order orthogonal iteration decomposition algorithm and factor matrix projection are used to remove redundant information duplicated inter-modal and produce fewer parameters with minimal information loss. The performance of the proposed method is verified by three different multi-modal datasets. The numerical results validate the accuracy of the performance of the proposed method having 0.4% to 4% improvement in sentiment analysis, 0.3% to 8% improvement in personality trait recognition, and 0.2% to 25% improvement in emotion recognition at three different multi-modal datasets compared with other 5 methods.     

基于近红外和中红外光谱数据融合以及竞争自适应重加权采样方法对甲维盐制剂中活性成分的测定

农药活性成分的快速测定已经成为农药质量监控的一个大趋势。通过融合甲维盐制剂近红外和中红外得光谱数据,旨在用数据融合的方法建立一种快速可靠的测定甲维盐制剂活性成分的方法。采用了将偏最小二乘回归法与数据融合相结合,以及用竞争自适应重加权采样法来选择偏最小二乘回归中的有效变量的方法。与近红外和中红外各自建立的模型相比,数据融合在吸取了近红外光谱和中红外光谱相互补充的信息后,具有协同效应的模型效果有了很大的提高。同时,证实了竞争自适应重加权采样法在建模过程中是一个使得模型更加简单高效的有效的变量选择技术。研究结果表明在吸收了不同来源的多种信息之后的数据融合是一种能提高模型效果的很有效的建模方法。数据融合策略的可行性使得测定低浓度(0.1%～1.0%)样品能获得更好的结果,而且结合了变量筛选算法的对近红外和中红外光谱的数据融合,是一个很有前景的测定商业农药制剂中有效成分的方法。最后建立了一种基于近红外光谱和中红外光谱数据融合来测定商业甲维盐制剂的有效成分的方法。     

Feature fusion of palmprint and face via tensor analysis and curvelet transform

In order to improve the recognition accuracy of the unimodal biometric system and to address the problem of the small samples recognition, a multimodal biometric recognition approach based on feature fusion level and curve tensor is proposed in this paper. The curve tensor approach is an extension of the tensor analysis method based on curvelet coefficients space. We use two kinds of biometrics: palmprint recognition and face recognition. All image features are extracted by using the curve tensor algorithm and then the normalized features are combined at the feature fusion level by using several fusion strategies. The k-nearest neighbour (KNN) classifier is used to determine the final biometric classification. The experimental results demonstrate that the proposed approach outperforms the unimodal solution and the proposed nearly Gaussian fusion (NGF) strategy has a better performance than other fusion rules.     

基于可能性分布联合落影的红外图像融合算法选取

针对双模态红外图像实际融合需求中常涉及到异类差异特征协同优化融合,且现有差异特征属性无法针对性地调整融合算法进行有效驱动,导致融合效果差等问题,提出了基于可能性分布联合落影的双模态红外图像融合算法选取的方法。首先计算双模态红外图像差异特征幅值的融合有效度,利用K最近邻法得到差异特征幅值的概率密度分布,得到差异特征频次属性的分布;然后通过差异特征幅值属性与频次属性构造差异特征权重函数,建立异类差异特征权重函数与多融合算法间的可能性分布合成,得到异类差异特征权重函数多融合算法融合有效度的联合落影;最后构建融合性能指标动态选取最优融合算法。实验结果表明,本文方法所选出的最优融合算法在等级得分指标上明显优于其他算法,验证了本文将可能性分布联合落影运用于双模态红外图像最优融合算法选取中具有可行性。     

Sensor fusion for active vibration isolation in precision equipment

Sensor fusion is a promising control strategy to improve the performance of active vibration isolation systems that are used in precision equipment. Normally, those vibration isolation systems are only capable of realizing a low transmissibility. Additional objectives are to increase the damping ratio of internal vibration modes and to provide a high support stiffness. It is shown that these three objectives cannot be realized simultaneously if only acceleration or force feedback is used. An active hard mount suspension with a feedback strategy based on sensor fusion is proposed that uses the acceleration signal at low frequencies and the force signal at high frequencies. Using sensor fusion, the three objectives can be achieved simultaneously. Experiments on a single-axis setup show that this feedback strategy provides an excellent performance.     

An uncertain information fusion method based on possibility theory in multisource detection systems

In multisource detection systems, the information representing detection characteristics is uncertain, also the relationship between detection characteristics and detection performance has uncertainty, meanwhile the influence degrees of each characteristic on the performance are also different. In order to represent and process these uncertain information effectively, this paper proposes an uncertain information fusion method based on possibility theory. Firstly, possibility distributions of a series of characteristic parameters about sensor information are constructed, and effective detection characteristics are extracted through the similarity measurement according to the similarity based on distances. The uncertain relationship between detection characteristics and detection performance is quantified, and a certainty calculation method of possibility distributions is proposed based on the combination of holistic and local characteristics. According to the above certainty, the weights of each characteristic are obtained to achieve the fusion of possibility distributions. Finally, the metallic and nonmetallic adhesive structure is taken as a case, and this case shows that this method not only considers the differences of the various characteristics contributed on adhesive performance, but also can achieve the fusion of possibility distributions under different situations. It is a more reasonable fusion method and fits the reality well in practice, also it provides new method and new idea for the fusion of possibility distributions.     

高速光通讯面发射激光器的热分析及优化

垂直腔面发射激光器(VCSEL)已成为短距离数据通信传输系统的首选光源。热限制是VCSEL器件调制带宽进一步增加的一个主要的制约因素。本文基于有限元分析的方法对影响980 nm-VCSEL器件有源区温度的参数,如驱动电流、氧化孔径尺寸、氧化层材料等做了比较分析,还数值分析了二元系Ga As/Al As材料DBR用于高速低能耗VCSEL器件的优势,为绿色光子器件设计提供优化思路。     

Effective contrast enhancement method for color night vision

Image fusion refers to the techniques that integrate complementary information from multiple image sensors’ data in a way that makes the new images more suitable for human visual perception. The paper focuses on the low color contrast problem of linear fusion algorithms with color transfer method. Firstly, the contrast of infrared and visible images is enhanced using local histogram equalization and median filter. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To enhance the color contrast between the target and the background, the scaling factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot and cold targets are all popped out with intense colors while the background details present natural color appearance. Target detection experiments through target recognition area, detection rate, target-background discrimination also show that the presented method has a better performance than the former methods.     

Fusion of deep shallow features and models for speaker recognition

In order to further improve the performance of speaker recognition, features fusion and models fusion are proposed. The features fusion method is to fuse deep and shallow features. The fused feature describes speaker characteristics more comprehensively than a single feature because of the complementarity between different levels of features. The models fusion method is to fuse i-vectors extracted from different speaker recognition systems. The fused model can combine advantages of different speaker recognition systems. Experimental results show the effectiveness of the proposed methods. Compared with the state-of-the-art system on CASIA North and South dialect corpus,the proposed features fusion system and models fusion system achieved about 54.8% and 69.5% relative improvement on the equal error rate(EER),respectively.     

Fast color contrast enhancement method for color night vision

The increasing availability and deployment of imaging sensors operating in multiple spectral bands has led to a large research effort in color image fusion, resulting in a plethora of pixel-level image fusion algorithms. In this study a simple and fast fusion approach for color night vision is presented. The contrast of infrared and visible images is adjusted by local histogram equalization. Then the two enhanced images are fused into the three components of a Lab image in terms of a simple linear fusion strategy. To obtain false color images possessing a natural day-time color appearance, this paper adopts an approach which transfers color from the reference to the fused images in a simplified Lab space. To enhance the contrast between the target and the background, a stretch factor is introduced into the transferring equation in the b channel. Experimental results based on three different data sets show that the hot targets are popped out with intense colors while the background details present natural color appearance. Target detection experiments also show that the presented method has a better performance than the former methods, owing to the target recognition area, detection rate, color distance and running time.     

具有紧支撑正交非张量积小波的图像融合

提出了基于一种新的小波——具有紧支撑、正交性、伸缩矩阵为[^2 0 ^0 2]的非张量积小波的图像融合方法。首先根据非张量积小波理论,利用Daubechies构造的单变量滤波器构造出基于四通道的不可分的小波滤波器组,用此滤波器组对参加融合的图像进行分解,然后对低频部分采用取均值、高频部分采用系数绝对值取大的融合算法对分解子图进行融合,最后重构。并采用熵、交叉熵、互信息、均方根误差和峰值信噪比等指标对该方法进行了客观评价。对可见光图像与红外图像、远红外图像与近红外图像、遥感图像、多聚焦图像和其它多类图像的融合实验结果证明本方法有较好的融合效果,其融合性能与采用同样融合算法的张量积db2小波的融合方法的融合性能相当。     

基于可能性信息质量合成的双模态红外图像融合算法选取

针对双模态红外图像在融合时异类差异特征两两合成出现信息冗余导致所选择的融合算法相互冲突,造成融合效果差甚至失效的问题,提出了一种基于可能性信息质量合成的双模态红外图像融合算法选取方法。首先计算双模态红外图像多融合算法下不同差异特征的融合有效度,利用可能性框架得到对应的可能性分布向量子集;其次计算向量子集的信息量和可信度,并对多个向量子集进行加权合成;然后构建基于信息质量的排序函数,得到每种融合算法下的非支配子集;最后构建多融合算法得分函数的联合分布对多种融合算法优化选择。实验结果表明,将基于质量来整合多个差异特征的方法运用于双模态红外图像融合算法选取中,所选出的融合算法在加权综合指标上高于其他算法均值55%以上,证明了本文方法的有效性和合理性;由多组实验算得本文方法平均耗时10.083 s,在时间效率上也符合实时图像融合应用的工程需求。     

A fusion method for infrared–visible image and infrared-polarization image based on multi-scale center-surround top-hat transform

This paper presents a fusion method for infrared–visible image and infrared-polarization image based on multi-scale center-surround top-hat transform which can effectively extract the feature information and detail information of source images. Firstly, the multi-scale bright (dark) feature regions of source images at different scale levels are respectively extracted by multi-scale center-surround top-hat transform. Secondly, the bright (dark) feature regions at different scale levels are refined for eliminating the redundancies by spatial scale. Thirdly, the refined bright (dark) feature regions from different scales are combined into the fused bright (dark) feature regions through adding. Then, a base image is calculated by performing dilation and erosion on the source images with the largest scale outer structure element. Finally, the fusion image is obtained by importing the fused bright and dark features into the base image with a reasonable strategy. Experimental results indicate that the proposed fusion method can obtain state-of-the-art performance in both aspects of objective assessment and subjective visual quality.     

A categorization method of infrared polarization and intensity image fusion algorithm based on the transfer ability of difference features

The fusion of infrared polarization and intensity image can significantly improve the detection performance of target, and the fused image is more suitable for human visual perception and further image-processing tasks. In this paper, a new categorization method of infrared polarization and intensity image fusion algorithm based on the transfer ability of difference feature is proposed. Firstly, the difference feature between two kinds of image and the characteristics of different fusion algorithms are analyzed and summarized. Second, an evaluation vector of fusion algorithm for difference feature transform ability is constructed. Thirdly, the transfer ability of fusion algorithm for difference feature is estimated by the evaluation vector, and the degree of transfer ability of fusion algorithm for difference feature is analyzed. Finally the fusion algorithms are classified by the degree of transfer ability of fusion algorithm for difference feature. The results shows that the proposed fusion algorithm categorization method helps select fusion algorithms in actual scene.     

矢量水听器垂直阵列数据融合高分辨方位估计算法

为了实现矢量水听器垂直阵列对目标的高分辨方位估计,提出了基于MUSIC子频带最优加权数据融合方法。该方法采用MUSIC算法对划分的各窄带信号进行方位估计,并在各子频带对多基元方位估计结果进行最优加权最小二乘融合处理,最后通过加权直方图统计法得到最终方位估计结果。对算法进行的仿真及海上试验数据处理结果表明:本文算法在方位估计精度、方位估计正确概率、多目标分辨以及对噪声子频带的抑制能力方面都优于单个基元MUSIC以及多基元复声强器融合算法。      

Multilevel region of interest guided bit allocation for multiview video coding

Multiview video coding (MVC) is an efficient compression scheme, by which the large amount of multiview video data can be effectively processed. However, it ignores the characteristics of the human visual system. In this paper, we propose a multilevel region of interest (ROI) based bit allocation strategy for MVC, which can take advantage of the visual redundancy to improve encoding efficiency. First, the macro block (MB) saliency is derived from depth information of the video sequence, and the multilevel ROI segmentation is conducted based on the MB saliency distribution. Then, the multiview video bit allocation strategy based on multilevel ROI is proposed. We have evaluated system performance with several multiview video sequences in JMVC 8.5 reference software. Experimental results show that the quality of ROIs has a considerable improvement when the bit rate consumed is kept consistent with JMVC. Meanwhile, the proposed MVC method can save bit rate while maintaining the overall image quality.