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.     

Effects of hydrological changes on cooperation in transnational catchments: the case of the Syr Darya

Water allocation along the Syr Darya River may be affected by climate change. Here we statistically model cooperation strategies, country profits, and sensitivity of cooperation, showing that the hydrological regime affects transboundary cooperation. Climate change in the twenty-first century may reduce glacial cover, and reducing stream flows, decreasing chances of cooperation and potentially raising conflicts. Comparison with other transboundary catchments in Central Asia indicates moderate-to-high risk of conflicts for the Syr Darya. A template is provided for assessment of the stability of cooperation in the Syr Darya basin, and in catchments similarly dependent on water availability.     

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.     

试谈中职游戏动漫专业对美工设计课程的能力要求

阐述了中职学校美工设计课程在教学设置中存在的问题,提出了相应的观点,论述了在中职学校美工设计课程的定位,培养具有一定综合素质和一技之长的中职学生。同时指出了传统的的教学课程结构已经不适应当今社会对人才培养目标的需要,必须进行课程改革,以适应社会发展的需求。     

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.     

试谈在中职游戏设计类专业进行游戏引擎教学研究

中职类学校的游戏设计类专业,应该让学生学习些简单的游戏引擎设计,让学生能全面感知游戏的构成,从而有利于学生的就业和未来的再学习。