Fingerprint enhancement by directional Fourier filtering

A new method of enhancing fingerprint images is described, based upon nonstationary directional Fourier domain filtering. Fingerprints are first smoothed using a directional filter whose orientation is everywhere matched to the local ridge orientation. Thresholding then yields the enhanced image. Various simplifications lead to efficient implementation on general-purpose digital computers. Results of enhancement are presented for fingerprints of various pattern classifications. A comparison is made with the enhancement used within the automated fingerprint identification system (AFIS) developed by the UK Home Office. Use of the proposed enhancement method leads to significant improvements in the speed and accuracy of the AFIS     

Pattern image enhancement by automatic focus correction

Optical analysis techniques are key tools for the failure analysis and defect localization in integrated circuits. Using a confocal laser microscope, it is possible to extract different pieces of information such as spatial distribution of signals or voltage waveforms. Blur is getting a more and critical issue as technology pitch is getting smaller, very close to resolution limits. Find the correct focus, is a recurrent problem to solve in optical microscopy. The expert has to correct the blur disrupting the image, by manually searching the good focus. By consequences, this step may take a long time to identify regions of interest in the circuit. With this purpose in mind, the aim of this paper, is to propose an automatic process estimating the out-of-focus blur parameters characterized by specific attributes. Proposed technique takes advantage of extracted features in the Discrete Cosine Transform (DCT) of blurred images. The blur information is identified and allows to recover the blur's kernel. Finally, the accuracy and the robustness of the suggested process is demonstrated on real blurred images.     

Video segmentation using genetic algorithms with automatic parameter adaptation

A novel genetic algorithm for video sequence segmentation is presented. The novelty of the approach is that the mating rates such as crossover rate and mutation rate are not constant, but spatio-temporally varying. Experimental results demonstrate the effectiveness of the proposed method.     

Foveation scalable video coding with automatic fixation selection

Image and video coding is an optimization problem. A successful image and video coding algorithm delivers a good tradeoff between visual quality and other coding performance measures, such as compression, complexity, scalability, robustness, and security. In this paper, we follow two recent trends in image and video coding research. One is to incorporate human visual system (HVS) models to improve the current state-of-the-art of image and video coding algorithms by better exploiting the properties of the intended receiver. The other is to design rate scalable image and video codecs, which allow the extraction of coded visual information at continuously varying bit rates from a single compressed bitstream. Specifically, we propose a foveation scalable video coding (FSVC) algorithm which supplies good quality-compression performance as well as effective rate scalability. The key idea is to organize the encoded bitstream to provide the best decoded video at an arbitrary bit rate in terms of foveated visual quality measurement. A foveation-based HVS model plays an important role in the algorithm. The algorithm is adaptable to different applications, such as knowledge-based video coding and video communications over time-varying, multiuser and interactive networks.     

具有频率展开点选择功能的改进型MPVL算法

在Krylov子空间基础上发展起来的MPVL算法已被广泛用来处理互连线的模型约减问题.当互连线模型包含电感时,频率展开点变得至关重要但却难以确定.为此,本文提出了一个简单而有效的频率展开点选择方法.对实际的互连线模型所做的数值实验结果证明了该准则的有效性和鲁棒性.     

Increasing throughput in dense 802.11 networks by automatic rate adaptation improvement

Rate control algorithms for commercial 802.11 devices strongly rely on packet losses for their adaptation. As a result, they give poor performance in dense networks because they are not able to distinguish packet losses related to channel error from packet losses due to collision. In this paper, we evaluate automatic rate adaptation algorithms in IEEE 802.11 dense networks. A certain number of works in the literature address this problem, but they demand modifications of the IEEE standard, or depend on some special feature not available in off-the-shelf devices. In this context, we propose a new automatic rate control algorithm which is simple, easy to implement, standards-compliant, and well-suited for crowded 802.11 networks. Our approach consists of measuring the contention level, inferring the collision probability, and choosing transmission rates which maximize throughput. Results from simulation and real experiments show throughput improvement of up to 100% from our mechanism.     

Reversible data hiding with automatic contrast enhancement using two-sided histogram expansion

Recently, reversible data hiding (RDH) has emerged into a new class of data hiding methods that enables exact retrieving of both embedded data and cover medium. In the present study, a novel automatic RDH method with contrast enhancement is proposed, in which the data is embedded through two-sided histogram expansion. Two-sided histogram shifting doubles the number of bits embedded at each iteration. Moreover, it preserves the mean brightness of the cover image and prevents it from over enhancement with less calculation. Experimental results on two sets of images show that the proposed method enhances the image contrast at an appropriate level without using a mean brightness controller during data embedding and provides higher information security compared to the existing RDH approaches.     

基于指纹采集的网络空间大规模侦测系统

随着信息化设备的更新换代,网络内部容易出现信息孤岛,造成IT资产管理混乱,进而影响信息系统的安全性和稳定性。基于指纹采集的网络空间大规模侦测系统通过采集网络空间的指纹信息,对网络设备组件进行识别,基于分布式架构设计并实现了大规模分布式侦测,极大提升了侦测速度和侦测效率。     

A floating-gate comparator with automatic offset adaptation for 10-bit data conversion

We present a novel voltage comparator that uses nonvolatile floating-gate charge storage for either offset ing or automatic programming of a desired offset. We exploit the negative feedback mechanism of pFET hot-electron injection to achieve fully automatic offset cancellation. The adaptation guarantees an input offset less than the input-referred noise level regardless of initial device offset for a typical 8.3% observed injection mismatch. In addition, we demonstrate the ability to accurately program a desired offset. The design has been fabricated in a commercially available 0.35-/spl mu/m process. Experimental results confirm the ability to reduce the variance of the initial offset by two orders of magnitude and to accurately program a desired offset with maximum observed deviation 728 /spl mu/V and typical deviation 109 /spl mu/V. The mean offset is reduced by a factor of 416 relative to fabricated chips directly from the foundry and by a factor of 202 relative to UV-irradiated chips. Adaptation is fast, with settling time typically under 50 ms and scaling inversely with the exponential of the injection voltage. We achieve controlled injection to accurately program the input offset to voltages uniformly distributed from -1 to 1 V. The comparator exhibits a 5 ns propagation delay and consumes 270 /spl mu/W.     

Delay statistics of cooperative automatic repeat request over wireless networks with link adaptation

This paper proposes a method to analyze the delay distribution at the transmitter side for cooperative diversity wireless networks with link adaptation, which uses decode‐and‐forward as a relay strategy. The equivalent end‐to‐end channel model is captured by a finite state Markov channel model representing the multiple states of the Nakagami fading channel, and the delay statistics are obtained by using matrix geometry method. Cooperative diversity wireless network has a better delay performance compared with noncooperation wireless network. Copyright © 2012 John Wiley & Sons, Ltd.     

小型太阳能自动追踪系统研制

太阳能资源丰富,为了能高效地收集太阳能,文章设计了小型太阳能自动追踪系统,可以从4个方位检测阳光,并对其光心进行实时追踪,大大提高了能源利用率。该系统采用自动化控制,通过单片机控制步进电机转动来调整电池板角度实现对太阳能的全方位监控,从而有效提高太阳板的光电转化效率,实现太阳能利用最大化,解决了太阳能利用不充分的问题。     

二维环的快速选取与自动识别

二维图形处理中,二维闭合环的选取和自动判别是问题关键.通过对二维图形进行网格划分,减少了环选取过程中浮点运算量,提高了环选取的速度.还给出了一种二维闭合环的自动识别算法,通过该算法,不需人工干预,可以自动生成环关系的树状拓扑结构,从而正确判别各环之间的拓扑关系.     

数字散斑时间序列相关三维面形测量中提高精度的方法

本文提出一种基于数字散斑时间序列相关三维面形测量法中提高测量精度的方法－多相关峰优化法。在数字散斑时间序列相关测量法中,当物体表面存在复杂细微结构时,被物体调制的散斑图中局部区域的散斑子图像会出现明显变形和局部阴影,这时相关曲线会出现多相关峰。由于相关值很低,这些相关峰对应高度都有可能是测量点的高度值。本文用特殊的算法对这些相关峰对应高度值进行辨别,找出最适合的高度值作为测量值,对测量结果进行优化。实验证明该方法对改善因局部区域的散斑子图像的变形和局部阴影影响而导致的测量误差具有非常显著的效果,使得数字散斑时间序列相关三维面形测量法能够用来测量复杂三维物体面形。     

Fuzzy logic-based automatic contrast enhancement of satellite images of ocean

In this paper, we evaluate the conventional contrast enhancement techniques [histogram equalization (HE), adaptive HE] and the recent gray-level grouping method and the fuzzy logic method in order to find out which of these is well suited for automatic contrast enhancement for satellite images of the ocean, obtained from a variety of sensors. All the techniques evaluated were based on the principle of transforming the skewed histogram of the original image into a uniform histogram. The performance of the different contrast enhancement algorithms are evaluated based on the visual quality and the Tenengrad criterion. The inter comparison of different techniques was carried out on a standard low-contrast image and also three different satellite images with different characteristics. Based on our study, we advocate that a modified fuzzy logic method elucidated in this paper is well suited for contrast enhancement of low-contrast satellite images of the ocean.     

穿山甲鳞片表面的几何形态特征及其性能

对穿山甲鳞片的形态和组成进行了分析.穿山甲鳞片表面整体呈现出纵向棱纹与横向凹槽交错变化的非等格几何网状形态,其中纵向棱纹较大、较多.扇形分布;横向凹槽较小、较少,且以一定深度切断纵向棱纹.利用扫描电镜及x射线能谱仪对材料的拉伸、冲击断口及成分进行了分析.结果表明冲击断口为脆性断口;穿山甲鳞片是由极细的棱柱结构单元和叠片结构单元混合形成的;穿山甲鳞片除含有大量的碳、氢、氧及氮元素外,硫、硅、铁、铝、钙5种元素的含量也相对较高,鳞片内层中舍有少量磷元素.在转盘式土壤磨料磨损试验机上,进行磨料磨损试验,结果表明磨料粒子滑动方向平行于穿山甲鳞片棱纹的试样与磨料粒子滑动方向垂直于棱纹的试样相比,具有较好的耐磨性;穿山甲鳞片表面的自由式磨料磨损量,随着磨料粒子尺寸或相对滑动速度的提高而增大.     

Ultrasound image segmentation with shape priors: application to automatic cattle rib-eye area estimation.

Automatic ultrasound (US) image segmentation is a difficult task due to the quantity of noise present in the images and the lack of information in several zones produced by the acquisition conditions. In this paper, we propose a method that combines shape priors and image information to achieve this task. In particular, we introduce knowledge about the rib-eye shape using a set of images manually segmented by experts. A method is proposed for the automatic segmentation of new samples in which a closed curve is fitted taking into account both the US image information and the geodesic distance between the evolving curve and the estimated mean rib-eye shape in a shape space. This method can be used to solve similar problems that arise when dealing with US images in other fields. The method was successfully tested over a database composed of 610 US images, for which we have the manual segmentations of two experts.     

联合特征增强和锚点自动生成的遥感图像高精度目标检测

目标检测是遥感图像处理领域中一项重要而具有挑战性的任务,针对遥感图像中目标尺度差异较大以及方向分布随机等导致的遥感图像多尺度目标检测精度较低问题,本文提出一种基于特征增强和锚点框自动生成模块的目标检测方法。该方法在ResNet50网络中加入可操控的空洞卷积模块,并以此为基础设计了增强特征金字塔网络,提高网络对于目标多尺度特征表达能力。在区域建议网络中利用锚点框自动生成模块自主学习锚点框的位置和形状,以此获得更为稀疏和高质量的候选区域。本文在NWPU VHR-10数据集和飞机目标数据集上与多种基于卷积神经网络的目标检测算法进行对比实验,结果表明,本文所提方法在两个数据集上的mAP均为最优,分别为99.2%和87.7%,该方法具有较强的尺度自适应能力,有效的提高了遥感图像多尺度目标检测的精度。      

弱对比度细节模糊增强的自动参数选择

针对广义模糊增强算法中参数选择的主观性,提出了一种模糊参数自动调整的方法。通过分析实验得出模糊参数对图像增强效果的重要性,给出一种用图像可检测边缘度和图像熵的熵值作为图像增强的评价标准,并根据这个标准实现了原来模糊增强算法中参数的自动选择,达到图像的自动增强,提高图像中弱边缘对比度的目的。最后通过实验证明算法的有效性。