共查询到18条相似文献,搜索用时 109 毫秒
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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。 相似文献
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针对基于"视频指纹"特征的视频检索算法在实际应用中存在视频亮度整体漂移、突变干扰以及视频再编辑的问题,提出了一种基于动态时间规划的视频特征检索改进算法.该算法在原"视频指纹"算法的基础上采用了新的视频检索策略:首先,对视频帧进行区域分割,将"视频指纹"由单分量扩展到多分量;然后,采用基于粒度的相似性比较算法,用比对每帧视频指纹的变化,取代比较视频指纹本身;最后,采用改进的动态时间规划算法进行视频特征匹配,定位目标视频.在算法评估中,建立了由74段广告视频和154段再编辑视频组成的测试集.通过试验证明,改进算法可以有效应对视频检索过程中的亮度整体漂移、突变干扰和视频再编辑问题,检索算法具有很好的鲁棒性. 相似文献
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针对室内无线电发射源的位置指纹定位问题,提出一种改进加权KNN定位算法。在分析现有定位算法的基础上,建立测试点和参考点的余弦相似度关系,并把该余弦相似度用作KNN在线定位计算的权重,计算出第一次加权质心定位结果,根据此结果判断是否进行二次加权来确定测试点最终的估计位置,最后进行算法的仿真测试。结果表明,较之传统位置指纹算法该算法定位准确度提高17%左右,不仅克服传统算法在发射源定位中由于在线阶段针对测试点接收到的信号强度不同造成的定位稳定性差的问题,还避免当存在离测试点较远的参考点时造成的定位误差大的问题。 相似文献
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针对中药三维荧光光谱信号非线性问题,应用局部线性嵌入算法(LLE)对补虚类中药三维荧光光谱信号进行特征提取。使用荧光光谱仪测得不同浓度的24味补虚类中药的三维荧光光谱和等高线光谱图,并利用总体平均经验模态分解(EEMD)算法进行降噪处理,在此基础上,采用LLE算法对经过降噪处理后的三维荧光光谱数据进行特征提取; 然后,应用随机森林(RF)算法对提取的特征向量进行分类识别。为了验证LLE算法的有效性,将其与主成分分析(PCA)算法进行比较。实验结果表明: LLE-RF组合算法分类准确率达95%,比PCA-RF算法分类准确率高,从而验证了该算法的有效性。 相似文献
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针对电容式传感器采集的指纹图像的特点,本文提出了一套完整的指纹图像预处理组合算法.该算法充分考虑到了采集到的指纹图像的质量和图像面积等问题,且从全局角度出发在当前原有算法基础上加入了两次滤波去噪来增强指纹纹线并有效消除噪声以得到更清晰准确的处理结果.算法首先对采集到的指纹图像采用边缘保持滤波法去除噪声;然后使用基于纹路方向性的Cabor滤波图像增强算法增强去噪后的指纹图像,减少因指纹旋转及平移因素造成的误差;接着对增强后的图像采用动态阈值法进行二值化处理并进一步地二次滤波去噪;最后采用基于形态学的细化算法对二值图像进行细化将其变为点线图.实验证明,通过该算法处理后的图像很好地保留了纹线的关键信息,有利于后续的指纹特征提取和匹配. 相似文献
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半导体指纹传感器图像质量评估方法 总被引:2,自引:0,他引:2
指纹图像的采集处于指纹识别系统的最前端,图像质量的好坏直接关系到系统的处理速度和准确性。针对目前广泛使用的半导体指纹传感器,根据指纹本身的固有特性,设计出一纽多通道Gabor滤波器对指纹图像进行分解和特征提取,并结合基本的图像质量评估指标进行质量分析和判断。实验结果表明:该算法能有效地判断半导体指纹传感器的图像质量,有助于提高自动指纹识别系统的整体性能。 相似文献
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《中国测试》2015,(8)
针对目前已有的嵌入式指纹识别系统往往采用手工提取,不能自动学习并提取识别所需的特征及识别正确率仍然不高的缺点,提出一种基于自动编码器(Auto Encoder)和LSSVM的指纹识别系统。首先,提出采用FPS200作为指纹传感器采集指纹数据,然后将采集的数据经过滤波和二值化等预处理,通过比较差异算法获得Auto Encoder中的权值和偏置等参数,从而得到训练好的Auto Encoder用于指纹图像特征提取。最后,将自动提取的特征进行训练和分类,将投票最多的分类作为指纹识别的结果。通过测试表明,系统能较精确地实现指纹识别,具有收敛速度快、正确识别率高和匹配时间短的优点。 相似文献
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针对指纹图像中的较大平移和旋转,提出了一种基于离散度和EBFNN的指纹分类方法.首先,对指纹图像进行离散小波变换获得特征空间.然后,对特征空间进行搜索得到不同维数下的优化特征组合,通过研究这些优化特征组合的散度值随维数的变化趋势,最终确定特征向量的构成.最后,以此特征向量训练EBFNN,完成指纹纹型分类,并在FVC2000和FVC2002-DB1上作了测试.实验结果表明,当隐层节点为11时 ,总的纹型辨识正确率可达91.45%,而且对指纹图像中的平移和旋转具有良好的鲁棒性,具有一定的实用价值. 相似文献
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基于指纹结构特征信息匹配的算法 总被引:5,自引:0,他引:5
为了克服指纹识别中常见的问题,本文提出一种基于指纹结构特征信息匹配的算法。该算法利用改进的Bresenham算法求得指纹分叉点间连线所穿越的脊线个数和分叉点结构特征信息,得到模板指纹和待识指纹的结构特征信息矢量数组;运用二分图的完美匹配算法,得到矢量数组的匹配度。对该匹配度进行评估,如果高于某一个闽值,则认为指纹匹配成功;否则,则认为不是同一指纹。该算法在实际应用中取得较好的效果。 相似文献
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针对WLAN室内定位采集指纹点工作量大且定位精度不高的问题,提出一种基于核模糊C均值聚类(kernelized fuzzy C-means,KFCM)、低秩矩阵填充(low-rank matrix completion,LMC)及最小二乘支持向量机(least squares support vector machine,LSSVM)的室内定位算法。首先将指纹点利用KFCM算法进行聚类,使待测点定位到一个区域内。在该区域里运用LMC理论,重构出具有高密度指纹点的指纹库。最后利用LSSVM定位出待测点的物理位置。实验结果表明,采用KFCM-LMC-LSSVM算法不仅减少了构建指纹库的工作量,而且提高了定位精度。 相似文献
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Biometric recognition refers to the identification of individuals through their unique behavioral features (e.g., fingerprint, face, and iris). We need distinguishing characteristics to identify people, such as fingerprints, which are world-renowned as the most reliable method to identify people. The recognition of fingerprints has become a standard procedure in forensics, and different techniques are available for this purpose. Most current techniques lack interest in image enhancement and rely on high-dimensional features to generate classification models. Therefore, we proposed an effective fingerprint classification method for classifying the fingerprint image as authentic or altered since criminals and hackers routinely change their fingerprints to generate fake ones. In order to improve fingerprint classification accuracy, our proposed method used the most effective texture features and classifiers. Discriminant Analysis (DCA) and Gaussian Discriminant Analysis (GDA) are employed as classifiers, along with Histogram of Oriented Gradient (HOG) and Segmentation-based Feature Texture Analysis (SFTA) feature vectors as inputs. The performance of the classifiers is determined by assessing a range of feature sets, and the most accurate results are obtained. The proposed method is tested using a Sokoto Coventry Fingerprint Dataset (SOCOFing). The SOCOFing project includes 6,000 fingerprint images collected from 600 African people whose fingerprints were taken ten times. Three distinct degrees of obliteration, central rotation, and z-cut have been performed to obtain synthetically altered replicas of the genuine fingerprints. The proposal achieved massive success with a classification accuracy reaching 99%. The experimental results indicate that the proposed method for fingerprint classification is feasible and effective. The experiments also showed that the proposed SFTA-based GDA method outperformed state-of-art approaches in feature dimension and classification accuracy. 相似文献
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Many applications require detection of multiple features that locally remain consistent in shape and intensity characteristics, but may globally change position with respect to one another over time or under different circumstances. We refer to these feature sets, defined by their characteristic relative positioning, as multifeature constellations. We introduce a method of processing in which multiple levels of correlation, using specially designed composite feature detection filters, are used to first detect local features, and then to detect constellations of these local features. We include experimental procedures and results indicating how the use of multifeature constellation detection may be utilized in applications such as sign language recognition and fingerprint matching. 相似文献
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An important step in the fingerprint identification system is the reliable extraction of distinct features from fingerprint images. Identification performance is directly related to the enhancement of fingerprint images during or after the enrollment phase. Among the various enhancement algorithms, artificial-intelligence-based feature-extraction techniques are attractive owing to their adaptive learning properties. We present a new supervised filtering technique that is based on a dynamic neural-network approach to develop a robust fingerprint enhancement algorithm. For pattern matching, a joint transform correlation (JTC) algorithm has been incorporated that offers high processing speed for real-time applications. Because the fringe-adjusted JTC algorithm has been found to yield a significantly better correlation output compared with alternate JTCs, we used this algorithm for the identification process. Test results are presented to verify the effectiveness of the proposed algorithm. 相似文献
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