基于图像场能分析的指纹图像增强

手指的脱皮老化以及活体指纹传感器带来的图像误差易影响指纹图像的成像质量.为此,针对低质量指纹图像中存在的纹线断裂、脊谷粘连以及手指脱皮造成的区域性模糊等问题,提出了一种基于指纹图像场能分析的指纹图像增强算法.算法分析和计算了指纹图像的强度场、梯度场、方向场和频率场,并在分析图像本身特点的基础上结合各场能具体信息以及Gabor滤波原理对指纹图像进行逐步的增强处理.实践表明,整套算法对低质量指纹图像增强效果良好,能大幅度提高指纹图像质量.     

基于图像场的指纹图像预处理算法研究与实现

指纹识别技术主要包括指纹图像预处理,指纹图像特征提取和指纹图像特征比对三大模块。作为指纹识别的关键技术之一,指纹图像预处理的质量好坏将直接影响到后续的处理过程和最终识别结果的正确性及可靠性。预处理的目的是尽量消除所采集到的指纹图像噪声,并将指纹骨架估计提取出来,以便进行指纹特征的提取工作。本文主要讲述了基于图像场的指纹图像预处理算法,主要包括基于图像场的指纹图像分割,滤波,二值化和细化等几个步骤,并且经由VC平台编程实现,以验证算法的有效性和可行性。     

结合遗传算法与方向图法的指纹图像分割

指纹作为人体的重要特征，由于其唯一性和终生不变性，越来越成为生物测定技术的重要手段，在自动指纹识别中，指纹图像分割是图像预处理中关键的一环，不仅能够对图像信息进行压缩，保留脊谷线的主要信息，同时能够去除大量的粘连，加速后续处理的速度和提高指纹特征提取和匹配的精度，将基于遗传算法的阈值分割方法和方向图法相结合对指纹图像进行分割。     

智能选取滤波器的方向图滤波算法

由于指纹图像纹线粗细的不同,分块大小固定及使用同一滤波器不能适用于不同的指纹图像。针对方向图滤波方法中,由于图像分块大小及滤波器不合适,导致不能连接图像中的断线,或是在曲率变化较大的图像区域出现“尖”的不平滑现象,提出了一种智能选取分块大小及滤波器的算法,该算法在大量的实验中,表明了其有效性。     

灰度值频数和遍历八方向的指纹图像分割算法

提出基于灰度值频数和遍历八方向的指纹图像分割算法。对于脊谷线灰度值相差较大的,利用灰度直方图上出现频数较多的两个灰度级的差值大小,判断是否为指纹前景区;脊谷线灰度值相差不大的,利用纹线的方向性,通过八个方向的模板计算在各个方向上灰度差值的大小,确定是否为指纹前景区。该方法的阈值可以根据图像自然决定,避免了人为选择阈值的困难和不准确性。对脊谷线灰度值相差较大、不大、较小的指纹图均能容易而准确地分割,只求出指纹的边界而不改变指纹图。实验表明,与常见的分割方法—方向图、方差法相比,该方法的平均误分概率大大减小,比方差法降低5.7875%,比方向图法降低5.6625%,且对指纹图像脊谷线的对比度和方向性要求不高,鲁棒性更强。     

基于Gabor滤波器的指纹图像增强

通过对传统指纹图像增强算法的研究,提出一种基于Gabor滤波的指纹图像增强算法。根据指纹纹线间距均匀且局部平行的特点,建立了用于指纹图像增强的Gabor滤波函数的物理模型,并利用二维Gabor滤波器可分解为正交方向的一维高斯带通滤波器和一维高斯低通滤波器的特点,将二维滤波分解为两次一维滤波,从而解决了计算量过大的问题,降低了算法的复杂度。实验表明该算法具有良好的增强指纹图像的脊线和抑制噪声的作用。     

指纹图像细化算法的改进

本文通过对指纹图像细化算法的分析研究,针对细化算法存在的问题,提出了一种在细化过程中能够使得骨架位于纹线中心的有效算法。实验结果表明,本文提出的改进算法,可以得到理想的指纹细化效果。     

基于方向滤波的指纹特征提取

对现有指纹图像增强算法进行研究,利用高斯滤波器的方向选择性,对正确求解出方向图的指纹图像进行方向滤波,很好的增强了指纹图像。对增强后的指纹图像进行细化,利用掩膜求解出指纹图像中的特征点。实验结果表明该方法可以很好的提取出指纹图像中的特征点。     

基于频率分级的指纹图像压缩算法

指纹图像是由黑白相间的脊线、谷线排列在一起而构成的特殊灰度图像,反复出现的反差边缘、周围的背景区域使得指纹图像具备低、中、高三种不同的频率成分,本文利用小波包变换和频谱分析提出了一种基于频率分级的指纹图像压缩算法,对包含能量最多的低频子图像,采用无损差分脉冲编码(DPCM)算法;对包含能量较少的中频子图像,采用嵌入式小波零数编码(EZW)算法;对包含能量最少的高频子图像,采用集合分裂嵌入块编码(SPECK)算法。仿真实验表明,本算法在保证重建质量的前提下,压缩比平均提高了21.4%左右,逼真度平均提高了6.25%左右。     

指纹细节特征提取与剪枝

指纹图像经预处理后，由于各种原因，会产生数以百计的特征。为了图像匹配的精确和快速，提出一套在细化后的指纹点线图上提取细节特征并对其剪枝的方法，并根据细节特征的拓扑特性，设计了验证其可靠性的算法。通过实验，证明了该后处理过程在去除指纹图像伪特征方法面具有良好的效果。     

Improved quadtree image segmentation approach to region information

Images are full of information and most often, little information is desired for subsequent processing. Hence, region of interest has key importance in image processing. Quadtree image segmentation has been widely used in many image processing applications to locate the region of interest for further processing. There are also variable block-size image coding techniques to effectively reduce the number of transmitted parts. This paper presents quadtree partition technique as a pre-processing step in image processing to determine what part should be more heterogeneous than the others. It also introduces an idea to solve the problem of squared images. Finally, proposed approach is implemented and analysed. The simulation of the Matlab code of the quadtree is represented by all algorithms and the figures. Thus, achieved results are promising in the state of the art.     

靶丸目标图象预处理

主要阐述了提取ＩＣＦ实验中靶丸目标边缘轮廓的图象处理方法。包括Ｓｏｂｅｌ边缘检测算子在内的多种方法都能够检测目标物体边缘及实验但未改进的算法在实验中效果不是很好。处理结果达到了实验的要求。     

Image denoising algorithms based on fractional sincα with the covariance of fractional Gaussian fields

Image denoising has been considered as an essential image processing problem that is difficult to address. In this study, two image denoising algorithms based on fractional calculus operators are proposed. The first algorithm uses the convolution of covariance of fractional Gaussian fields with the fractional sinc_α (FS) (sinc function of order α). The second algorithm uses the convolution of covariance of fractional Gaussian fields with the fractional differential Heaviside function, which is the limit of FS. In the proposed algorithms, the given noisy image is processed in a blockwise manner. Each processed pixel is convolved with the mask windows on four directions. The final filtered image based on either FS or fractional differential Heaviside function (FDHS) can be obtained by determining the average magnitude of the four convolution test results for each filter mask windows. The outcomes are evaluated using visual perception and peak signal to noise ratio. Experiments prove the effectiveness of the proposed algorithms in removing Gaussian and Speckle noise. The proposed FS and FDHS achieved average PSNR of 28.88, 28.26?dB, respectively, for Gaussian noise. The improvements outperform those achieved with the use of Gaussian and Wiener filters.     

基于最优模型残差的指纹方向校正法

指纹的方向信息是指纹图像处理中非常重要的信息，指纹方向场的获取以及校正直接影响指纹自动识别的性能。本文提出了一种基于指纹方向场数学模型的方向校正方法，根据指纹中的奇异点性质和分布，建立起与对应指纹方向场的最优方向场模型；然后，根据模型与实际指纹方向场的残差对指纹方向进行校正。由于算法利用指纹整体的拓扑信息对指纹噪声方向进行校正，具有很强的抗干扰能力，较适合劣质指纹图像处理。     

由序列图像进行三维测量的新方法

目前的三维测量方法都需要专门的测量设备且存在着种种限制,为此提出了一种基于图像序列进行三维测量的新方法。将由数码相机围绕被测物体拍摄的多幅图像导入计算机,利用图像处理知识得到特征的二维信息;采用计算机视觉方法,对特征从射影空间到欧式空间分层逐步重建即可完成三维测量。设计一套特征标志组合,作为辅助测量工具避免了特征匹配难题。确立了一套图像分割与识别策略获得特征标志二维信息,识别率可达到95%以上。采用基于模约束的摄像机分层自标定方法得到特征在欧式空间下的三维信息,并通过多种优化方法减少误差的影响。该方法在硬件上实现简单,对测量条件要求不高。实际试验表明,相对误差可达到1.48%,重投影误差为0.3864像素。     

A Full Fingerprint Verification System for a Single-Line Sweep Sensor

This paper presents a full fingerprint verification system. It is composed of a tactile fingerprint sensor, integrated read out and conversion circuits, and dedicated recognition algorithms. The sensor is a single-line sweep mode sensor, e.g., it is made of a single line of sensing elements, thus covering the minimum surface of silicon. Compared with cm² sized touch sensors, it offers a large cost reduction and possibility of easy integration into portable devices. The use of a single line to measure a fingerprint requires the user to sweep its finger along the sensor. This sensing scheme produces fingerprint images with several distortions that needs further image processing to allow efficient fingerprint recognition. This is why we developed and present here specific algorithms to take care of the sensor's specifications. This paper will present measurement results, as well as a performance evaluation of the entire verification system.     

WISECODE: wise image segmentation based on community detection

Image segmentation is one of the fundamental problems in image processing and computer vision, since it is the first step in many image analysis systems. This paper presents a new perspective to image segmentation, namely, segmenting input images by applying efficient community detection algorithms common in social and complex networks. First, a common segmentation algorithm is used to fragment the image into small initial regions. A weighted network is then constructed. Each initial region is mapped to a vertex, and all these vertices are connected to each other. The similarity between two regions is calculated from colour information. This similarity is then used to assign weights to the edges. Afterwards, a community detection algorithm is applied, and communities are extracted such that the highest modularity measure is achieved. Finally, a post-processing algorithm merges very small regions with the greater ones, further enhancing the final result. One of the most striking features of the proposed method, is the ability to segment the input image without the need to specify a predefined number of segments manually. This remarkable feature results from the optimal modularity value, which is utilised by this method. It is also able to segment the input image into a user defined number of segments. Extensive experiments have been performed, and the results show that the proposed scheme can reliably segment the input colour image into good subjective criteria.     

基于图像清晰度评价的摄像头辅助调焦系统

提出一种新的图像清晰度(包括锐度和对比度)评价函数,对比传统的图像清晰度评价算法,新算法速度最快且准确,以及和功率谱算法一样优良的灵敏度,适合各种实时自动对焦系统.本文使用一系列不同程度的离焦图片演示了所有算法的性能。同时将新算法应用于一种实际的摄像头模块辅助调焦系统中,系统把采集的每帧图像实时显示在屏幕上,用新算法评价图像的清晰度,从而指导作业员对摄像头模块进行调焦。实践表明该摄像头辅助调焦系统在批量生产摄像头模块时对提高生产效率和稳定质量方面有很大作用。     

一种快速检测光滑半球表面缺陷的方法

针对具有镜面反射特性的光滑球面,提出了一种利用反光带的镜像变形来对表面缺陷进行快速检测的新方法。这种方法通过漫反射反光带增强图像上的缺陷信息,克服了背景噪声在图像处理中会造成较大误差的缺点,也降低了照明系统的设计难度。根据缺陷引起的反光带镜像变形获取缺陷特征,使图像处理软件的工作量大大减少。通过实验,给出了缺陷尺寸和扫描间隔等因素对检测结果影响的分布曲线,为合理提取缺陷尺寸提供了参考。实验表明,该方法的鲁棒性好、效率高,能识别0.5mm以上的全部缺陷,定位误差在 1之内。