一种面向大规模短特征集的字符串匹配技术

面向大规模特征集的字符串匹配技术在病毒检测、内容过滤等问题上的应用愈加广泛,而短模式串一直是阻碍性能提升的重要瓶颈。针对短模式串进行分析讨论,基于跳跃算法优化,采用了动态块大小和动态Hash处理以及Hash函数设计场景化的策略,同时探讨了多核处理器与多线程设计之间的关系。实验数据证明改进的算法策略具有支撑百万级特征集字符串匹配的能力。     

多尺度空间特征提取的脊柱图像拼接算法

针对脊柱图像视野有限,提出一种基于优化MSFE的脊柱图像自动拼接算法。设计出一种基于尺度因子变化的高斯卷积模板尺寸自适应调整以及双向配对办法;相似性度量采用城市距离;利用RANSAC算法去除错配,从而确定待拼接图像之间的变换参数,最后利用加权平均对图像融合。对实际取得的多幅脊柱图像拼接结果表明该算法具有很好的实时性和鲁棒性。     

Gradient orientation pattern matching with the Hamming distance

This paper presents a novel pattern matching technique that is robust to illumination changes and the occlusion problem. The technique is based on the matching of gradient orientations in place of traditional image features such as intensities or gradients. Gradient orientations depend on the texture in an image. They are known to be insensitive to changes of image intensities that are often caused by time-varying illuminations or the auto-gain control (AGC) function of the camera. Moreover,the proposed method employs a voting strategy in the process of matching gradient orientations. The method works remarkably well even when a large part of the pattern is occluded with a foreign object. Consequently, the proposed method is robust to both irregular lighting conditions and the occlusion problem.     

Nighttime face recognition at large standoff: Cross-distance and cross-spectral matching

Face recognition in surveillance systems is important for security applications, especially in nighttime scenarios when the subject is far away from the camera. However, due to the face image quality degradation caused by large camera standoff and low illuminance, nighttime face recognition at large standoff is challenging. In this paper, we report a system that is capable of collecting face images at large standoff in both daytime and nighttime, and present an augmented heterogeneous face recognition (AHFR) approach for cross-distance (e.g., 150 m probe vs. 1 m gallery) and cross-spectral (near-infrared probe vs. visible light gallery) face matching. We recover high-quality face images from degraded probe images by proposing an image restoration method based on Locally Linear Embedding (LLE). The restored face images are matched to the gallery by using a heterogeneous face matcher. Experimental results show that the proposed AHFR approach significantly outperforms the state-of-the-art methods for cross-spectral and cross-distance face matching.     

HEGM: A hierarchical elastic graph matching for hand gesture recognition

A hierarchical scheme for elastic graph matching applied to hand gesture recognition is proposed. The proposed algorithm exploits the relative discriminatory capabilities of visual features scattered on the images, assigning the corresponding weights to each feature. A boosting algorithm is used to determine the structure of the hierarchy of a given graph. The graph is expressed by annotating the nodes of interest over the target object to form a bunch graph. Three annotation techniques, manual, semi-automatic, and automatic annotation are used to determine the position of the nodes. The scheme and the annotation approaches are applied to explore the hand gesture recognition performance. A number of filter banks are applied to hand gestures images to investigate the effect of using different feature representation approaches. Experimental results show that the hierarchical elastic graph matching (HEGM) approach classified the hand posture with a gesture recognition accuracy of 99.85% when visual features were extracted by utilizing the Histogram of Oriented Gradient (HOG) representation. The results also provide the performance measures from the aspect of recognition accuracy to matching benefits, node positions correlation and consistency on three annotation approaches, showing that the semi-automatic annotation method is more efficient and accurate than the other two methods.     

Fast fingerprint identification for large databases

Fingerprint matching has emerged as an effective tool for human recognition due to the uniqueness, universality and invariability of fingerprints. Many different approaches have been proposed in the literature to determine faithfully if two fingerprint images belong to the same person. Among them, minutiae-based matchers highlight as the most relevant techniques because of their discriminative capabilities, providing precise results. However, performing a fingerprint identification over a large database can be an inefficient task due to the lack of scalability and high computing times of fingerprint matching algorithms.In this paper, we propose a distributed framework for fingerprint matching to tackle large databases in a reasonable time. It provides a general scheme for any kind of matcher, so that its precision is preserved and its time of response can be reduced.To test the proposed system, we conduct an extensive study that involves both synthetic and captured fingerprint databases, which have different characteristics, analyzing the performance of three well-known minutiae-based matchers within the designed framework. With the available hardware resources, our distributed model is able to address up to 400 000 fingerprints in approximately half a second. Additional details are provided at http://sci2s.ugr.es/ParallelMatching.     

k-NN classification of handwritten characters via accelerated GAT correlation

This paper addresses the problem of reinforcing the ability of the k-NN classification of handwritten characters via distortion-tolerant template matching techniques with a limited quantity of data. We compare three kinds of matching techniques: the conventional simple correlation, the tangent distance, and the global affine transformation (GAT) correlation. Although the k-NN classification method is straightforward and powerful, it consumes a lot of time. Therefore, to reduce the computational cost of matching in k-NN classification, we propose accelerating the GAT correlation method by reformulating its computational model and adopting efficient lookup tables. Recognition experiments performed on the IPTP CDROM1B handwritten numerical database show that the matching techniques of the simple correlation, the tangent distance, and the accelerated GAT correlation achieved recognition rates of 97.07%, 97.50%, and 98.70%, respectively. The computation time ratios of the tangent distance and the accelerated GAT correlation to the simple correlation are 26.3 and 36.5 to 1.0, respectively.     

An efficient parallel-network packet pattern-matching approach using GPUs

In the past few years, the increase in interest usage has been substantial. The high network bandwidth speed and the large amount of threats pose challenges to current network intrusion detection systems, which manage high amounts of network traffic and perform complicated packet processing. Pattern matching is a computationally intensive process included in network intrusion detection systems. In this paper, we present an efficient graphics processing unit (GPU)-based network packet pattern-matching algorithm by leveraging the computational power of GPUs to accelerate pattern-matching operations and subsequently increase the overall processing throughput. According to the experimental results, the proposed algorithm achieved a maximal traffic processing throughput of over 2 Gbit/s. The results demonstrate that the proposed GPU-based algorithm can effectively enhance the performance of network intrusion detection systems.     

Matching ratio between positive and negative electrodes for double-layer capacitors

For double-layer capacitors in alkaline electrolyte, the specific capacitance of the positive electrode is not equal to that of the negative one. Thus, capacitor performance cannot be optimal with a positive/negative electrode matching ratio of 1. In this study nanoporous glassy carbons (NPGCs) were employed as the electrodes of capacitors, and the influence of matching ratio between positive and negative electrode on capacitor performance was systematically investigated. In aqueous KOH, the specific capacitance of the positive electrode is lower than that of the negative electrode. The matching ratio at which a maximum capacitance is obtained is dependent on the values of the positive and negative electrode capacitance. At low current rate, the highest specific capacitance is achieved at a matching ratio slightly higher than 1. At high current rate, a capacitor has the highest specific capacitance with the lowest resistance at a matching ratio of 1.5. This indicates that an optimum matching relationship between positive and negative electrodes is attained.     

到达数据中时空异常聚簇发现

在时空数据中有一类表示用户在某一时间到达某一地点的数据——到达数据,到达数据可以是社交网站的签到数据、轨迹数据中的停留点及公共交通中乘客抵达的位置数据,这些数据的聚簇可以反映用户的聚集行为.基于到达数据,提出一类新的时空数据查询——时空异常聚簇发现.将到达数据进行周期性划分,通过时空聚类算法对一个时间段的数据进行聚类,比较不同时间段内聚簇的差异度,发现具有最大簇异常度的前k个簇.通过该查询发现的时空异常聚簇可以应用于城市安全管理、基于位置的服务和交通调度等方面.定义了异常簇查询模型,提出了针对任意形状聚簇的簇差异度度量,将异常簇查询转化为二分图最大匹配问题,对二分图构建与匹配进行了优化并提出了高效的查询算法.利用真实数据集进行了充分实验,验证了查询结果的实际意义,评估了所提出的各查询算法在不同参数设置下的查询效率.