基于多传感器的人民币纸币鉴伪方法

人民币纸币真伪的判断对银行等金融部门非常重要,单一功能鉴伪对有些假钞鉴别已无能为力。为了提高点钞机等纸币清分仪器辨伪的准确度,应运用多种辨伪技术和检测手段。提出了一种以AT89C51为核心的,基于荧光、磁性、红外多传感器综合的人民币纸币鉴伪方法。介绍了鉴伪原理,设计了各鉴伪电路硬件及软件实现策略。     

一种基于边缘特征的纸币污损检测方法

污损检测是纸币清分中的一个重要环节 .针对纸币上常见的笔迹及撕裂污损,提出了一种基于图像边缘特征的检测方法 .首先将待检测图像与参考图像进行图像配准,然后采用Kirsch算子提取两图像的边缘信息,并提出了一种符合人的主观感受的边缘强度差的计算方法,在此基础上提取的污损特征,对于图像中新增加的边缘信息十分敏感,而对各像素的灰度值、边缘强度值的相对变化则具有很强的抗干扰性 .将纸币划分为若干个相互重叠的子区域,通过对子区域内污损特征统计,来判定该子区域内是否存在污损 .实验证明,该方法识别率高且稳定、可靠,满足实际要求 .该方法已应用到实际的纸币清分系统中 .     

电涡流式纸币厚度传感器设计

点钞机主要依靠磁性安全线、磁性油墨、光学特征等特征来识别伪钞,部分伪钞或残旧钞票粘贴有大小、位置不同的透明胶纸也要区分,难以通过现有技术识别。设计了一种多段机械式厚度传感器,将纸币的厚度转化为机械位移,利用基于TI公司的LDC1000电感数字转换器组成的精密位移传感器实现纸币不同部位厚度的定位检测。首先阐述了机械式厚度传感器的结构与工作原理,并介绍采用TI公司提供的WEBENCH?Designer LDC1000工具设计传感器电路系统。初步试验结果表明,该传感器可在1 mm检测范围内达到优于5μm的分辨率,检测速率达到10 kHz,满足纸币厚度检测要求。     

红外方式数字图像采集报警系统的设计

介绍了AT91SAM7S64单片机的主要特点和性能,分析了采用该芯片减少及优化外围电路,提高精度、实时性和可靠性等方面的优势.着重阐述了应用该芯片实现红外控制、自动摄像的软、硬件设计方案,分析了为提高实时性而在软硬件设计方面所采取的措施.     

红外弱小目标预处理及检测方法研究

本文针对红外弱小目标检测问题,通过分析研究多种红外小目标检测的预处理方法。提出了一种能有效检测出低信噪比条件下运动小目标的算法,并给出了相应的实验结果。     

纸币号码识别中分割方法的研究

针对纸币号码识别过程中图像分割存在的问题,提出了一种逻辑脊谷判断的图像分割方取号码线条,经过简单的迭代法二值化和数学形态学闭运算处理,分割线条清晰准确,算法简单,算法与本文算法比较．本文算法处理速度快,分割图像准确。     

电力设备红外温度在线监测装置的设计

目前随着变电设备在线监测技术的推广,红外温度在线监测必将广泛应用于电力设备状态检修.本文提出基于FPGA/SOPC的电力设备红外温度在线监测装置的设计,内置NIOS软核,实现红外机芯组件驱动、采集控制、数据处理传输均在FPGA中进行,减少了装置的复杂度,提高了稳定性,实现红外温度数据实时采集,易于及时发现存在过热性缺陷的设备,提高了电力设备的可维护性.     

基于FPGA的红外图像高速采集及预处理电路

介绍了基于FPGA的红外视频图像高速采集及预处理电路的总体结构。电路采用了模块化结构设计、流水线工作方式及乒乓存储等多项技术。该电路与TMS320C6414通过HPI口高速通信保证了数据传输的实时性。详细介绍了图像采集、HPI接口等模块的工作原理及实现方法。经实验,该电路实现了对数字PAL式16位数字图像的采集及背景抑制,分担了大量后续处理机的计算工作,极大地提高了系统的实时性。     

舰船红外图像边缘检测方法对比研究

为了对海上舰船红外图像进行分割和目标识别,首先具体分析了六种边缘检测算子Roberts算子、Prewitt算子、Sobel算子、Log算子、Kirsch算子、Canny算子的检测原理,给出了各种检测算子的计算模板。然后采用Roberts算子、Prewitt算子、Sobel算子、Log算子、Kirsch算子、Canny算子对舰船红外图像进行处理,分析比较各个检测算法的检测优缺点。最后用Matlab语言编程实现各种检测算法,通过Matlab软件进行仿真实验,用各种检测算法处理舰船红外图像,直观的给出各检测算子的舰船图像处理效果,并对处理结果进行了比较,得出了在噪声干扰下,Canny算子更容易处理舰船红外图像的结论。     

运动目标检测的红外与可见光图像融合方法

在弱可见光条件下,对同一场景监控的红外与可见光图像进行融合,使融合图像即显示红外目标,又能保留可见光图像的细节结构信息,方便观察者对场景的观察与监控。充分利用红外成像的特点,热目标与背景的温度差会使目标在红外图像中的灰度值更大。使用红外序列建立稳定的背景模型,当前帧与背景的差得到运动目标区域,然后,将目标区域内的红外目标融合到可见光图像中,达到对红外运动目标检测的目的。     

基于FPGA的高速信号采集板卡的设计

传统模拟信号采集板卡的低通信速率已成为高性能飞控测试系统功能的"瓶颈",针对这一问题,设计了一种以FPGA为核心的总线型高速数据采集板卡.板卡中信号调理电路有效抑制了模数转换中的零点温度漂移等问题,专用的模数转换芯片提高了采集精度.BLVDS总线与Modbus协议的应用使板卡具有模块化、网络化的功能.设计过程中充分利用...     

基于脆弱性数字水印的图象完整性验证研究

计算机网络技术的飞速发展与信息媒体的数字化 ,使得在网络环境中对数字产品实施有效的内容保护成为一个迫在眉睫的现实问题 .传统的数字签名技术只是用于对通信领域的信息传送进行篡改检测 ,而脆弱性数字水印技术则为网络环境下多媒体的内容保护提供了一个有效的解决方案 .与鲁棒性水印不同的是 ,脆弱性水印主要用于检测发生在多媒体数据中的篡改 ,并对其定位 .为了推动我国在此前沿领域研究工作的进一步深入 ,这里就当前脆弱性数字图象图象水印技术的基本特征、一般原理、研究现状、攻击方法及发展方向进行一个综述 .     

A secure and flexible authentication system for digital images

Authentication of image data is a challenging task. Unlike data authentication systems that detect a single bit change in the data, image authentication systems must remain tolerant to changes resulting from acceptable image processing or compression algorithms while detecting malicious tampering with the image. Tolerance to the changes due to lossy compression systems is particularly important because in the majority of cases images are stored and transmitted in compressed form, and so it is important for verification to succeed if the compression is within the allowable range.In this paper we consider an image authentication system that generates an authentication tag that can be appended to an image to allow the verifier to verify the authenticity of the image. We propose a secure, flexible, and efficeint image authentication algorithm that is tolerant to image degradation due to JPEG lossy compression within designed levels. (JPEG is the most widely used image compression system and is the de facto industry standard.) By secure we mean that the cost of the best known attack againt the system is high, by flexible we mean that the level of protection can be adjusted so that higher security can be obtained with increased length of the authentication tag, and by efficient we mean that the computation can be performed largely as part of the JPEG compression, allowing the generation of the authentication tag to be efficiently integrated into the compression system. The authentication tag consists of a number of feature codes that can be computed in parallel, and thus computing the tag is effectively equivalent to computing a single feature code. We prove the soundness of the algorithm and show the security of the system. Finally, we give the results of our experiments.     

一种基于可逆数字水印的图像认证方案

针对医疗图像、遥感图像等敏感数字图像在认证水印的嵌入过程中不能引入失真的特点,提出一种基于可逆数字水印的图像完整性认证方案:首先提取图像特征,将其作为hash函数的输入;再用图像发送者的私钥对hash值进行数字签名;最后将数字签名作为水印数据,利用图像相邻像素点差值直方图的特征,轻微改变图像像素点的灰度值来可逆嵌入水印数据。方案实现简单,水印嵌入后图像失真小,认证通过后还可以完全恢复原始图像。理论和实验证明水印嵌入后,PSNR值能达到51.14dB以上。     

基于小波变换的图象认证的数字水印技术

目前,基于小波变换的图像认证的数字水印技术已成为信息领域的研究热点。本文较全面地介绍了基于小波变换的图像认证数字水印技术的发展现状,给出了小波变换水印系统的基本结构、性能要求以及各种算法,并对算法进行了分析,总结了其优缺点。     

An image authentication method by applying Hamming code on rearranged bits

In 2007, Chan and Chang proposed an image authentication method using the Hamming code technique. The parity check bits were produced from pixels by using the Hamming code technique, and the produced bits were embedded in other pixels. When recovering, the method had to predict the value of the most-significant bit of each tampered pixel first. Then, the tampered pixel was able to be recovered by referring to the predicted bit and its parity check bits. However, using the most-significant bit is unsuitable because of the risk of making an incorrect prediction. In this paper, the parity check bits are produced from pixels whose bits have been rearranged. This way, the value of the most-significant bit of each tampered pixel can be determined according to its parity check bits. The recovery procedure is also modified to accommodate the rearranging procedure. The experimental results show that the proposed method has a better ability to recover the tampered areas, compared with Chan and Chang’s method. Moreover, the quality of the authenticated images of the proposed method is also higher than that of Chan and Chang’s method.     

A new approach for inner-knuckle-print recognition

ObjectiveThis paper proposed a new approach for inner-knuckle-print (IKP) recognition. In traditional IKP recognition systems, the region of interest (ROI) is extracted from the image of the whole hand and the directions of the fingers being imaged are not restricted. The result maybe incorrect because that the shape and surface of the fingers may vary greatly. Moreover, if the direction of the finger being imaged is not restricted, there may be severe rotation transform between intra-class IKPs. To overcome these drawbacks, we develop a new data acquisition scheme as well as an efficient personal authentication algorithm.MethodsThe new scheme is designed to capture the image of the inner surface of the middle knuckles of the middle and ring fingers. The fingers being imaged are kept horizontal with two pegs, so that the rotation angle between different images obtained from the same hand can be minimized. The new personal authentication algorithm consists of the next four steps. Firstly, two regions of interest (ROI), each of which contains the inner surface of a knuckle, are cropped from the original image. Secondly, line features are extracted from the ROIs based on the combination of Gabor filtering and derivative line detection method. Then, binary line images are matched by using a cross-correlation-based method. Finally, the input data is classified through score level fusion.ResultsTo evaluate the proposed IKP recognition system, a finger image database which includes 2000 images from 100 volunteers is established. The images are captured on two separate occasions, at an interval of around two months. Most of the volunteers are not familiar with the image acquisition process. The experimental results show that the proposed system achieves high recognition rate and it works in real time. Moreover, the proposed line feature extraction method outperforms traditional Gabor filter based line detection method and derivative line detection method in accuracy.ConclusionThe proposed IKP system is robust and accurate. It may promote the application and popularization of IKP recognition.     

基于跨层优化资源分配的图像流认证方法

图像流认证的丢包鲁棒性问题是图像认证研究的难题之一。现有的流级认证算法通常是在信源-信道分离编码条件下针对某种特定的图像编码方式而设计的,在抵抗丢包能力方面具有很大的局限性。针对上述问题,提出一种丢包鲁棒的图像认证优化模型,并在此基础上提出了在信源-信道联合编码条件下实现信源-认证-信道码率的跨层优化资源分配（Cross-Layer Optimization Resource Allocation,CLORA）方法。首先以可信图像的端到端质量和认证代价为优化目标,结合基于图认证和基于前向纠错码（Forward Error Correction,FEC）认证方法,建立认证优化模型（Authentication Optimization Model,AOM）,将图像认证的抗丢包优化问题等价成构造最优认证图（Optimal Authentication Graph,OAG）。然后利用图像码流的编码相关性和认证相关性,给出了求解OAG问题的等价条件,并在低计算复杂度下给出了构造OAG图的两个原子操作。最后提出了基于CLORA框架的认证优化方法。由于AOM模型仅利用码流的编码相关性信息,因而可以适用于不同的图像编码算法。JPEG 2000码流的实验结果表明,在相同丢包率下本文算法的端到端可信质量比已有算法平均提高了1.6dB,能够获得更优的丢包鲁棒性和端到端率失真（Rate-Distortion,R-D）性能。     

基于整数小波变换的图像鉴定数字水印技术

该文提出了一种基于整数小波变换的数字水印技术。首先,由原始图像边缘图的 Ｈａｓｈ函数输出的信息摘要比特流生成水印序列。然后,提出了一种整数小波域利用平移窗的多比特水印嵌入的非线性方法,并实现了脱离原始图像的具有高概率检测能力的水印检测方法。实验结果表明这是一种行之有效的图像鉴定方法。     

Color image watermark extraction based on support vector machines

This work proposes a novel watermarking technique called SVM-based Color Image Watermarking (SCIW), based on support vector machines (SVMs) for the authentication of color images. To protect the copyright of a color image, a signature (a watermark), which is represented by a sequence of binary data, is embedded in the color image. The watermark-extraction issue can be treated as a classification problem involving binary classes. The SCIW method constructs a set of training patterns with the use of binary labels by employing three image features, which are the differences between a local image statistic and the luminance value of the center pixel in a sliding window with three distinct shapes. This set of training patterns is gathered from a pair of images, an original image and its corresponding watermarked image in the spatial domain. A quasi-optimal hyperplane (a binary classifier) can be realized by an SVM. The SCIW method utilizes this set of training patterns to train the SVM and then applies the trained SVM to classify a set of testing patterns. Following the results produced by the classifier (the trained SVM), the SCIW method retrieves the hidden signature without the original image during watermark extraction. Experimental results have demonstrated that the SCIW method is sufficiently robust against several color-image manipulations, and that it outperforms other proposed methods considered in this work.