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surf tracking
- Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motion-based tracking framework which makes no such assumptions. Object is represented by
LBPdetect.rar
- local binary pattern特征是一种光照鲁棒的纹理算子,这是计算该特征的VC程序 ,local binary pattern feature is a light texture robust operator, which is to calculate the characteristics of the VC program
palm.rar
- ：首次提出将局部二进制模式(LBP)~-用到掌纹识别中。借鉴分级检索的思想，先采用Gabor滤波器提取掌纹的全局能量特 征．后采用LBP算子提取局部特征实现两次分类。实验结果表明，与单纯的Gabor滤波器方法相比，系统的识别率可进一步提高。,This paper first presents a new method of palmprint identification by using Local Binary Pattern (LBP)·By referring to hierarch
SURF
- 尺度不变局部特征提取，对于局部细节特征有很好的描述，具有旋转尺度不变性-Scale-invariant local feature extraction, feature for the local details are well described, with a rotating scale invariance
FingerPrintVerify
- 这是一个用C++语言实现一个指纹识别程序，要求满足FVC国际竞赛标准，并在学校建立的指纹库上实测。程序里应用到的技术有：中值滤波、直方图均衡化、脊线方向提取、Gabor滤波、指纹细化、特征提取、特征点过滤、基于局部特征点的特征匹配-This is a C++ Language realization of a fingerprint identification procedure, the requirements FVC meet international competition stan
InvariantLocalFeatureforImageMatching
- Invariant Local Feature for Image Matching,主要是介绍了一下图像副本检测的系统，先对图像提取sift特征，再用LSH匹配-Invariant Local Feature for Image Matching, mainly introduced a copy of what the image detection system, first sift the characteristics of the image extraction, and the
siftpaper
- SIFT特征匹配算法研究,sift讲义,Local grayvalue invariants for image retrieval-SIFT feature matching algorithm, sift lectures, Local grayvalue invariants for image retrieval
KernelBasedObjectTracking
- A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel.
kernel
- Kernel-based 图像去噪和复原算法，是一种基于图像局部特征的复原方法。-Kernel-based algorithm for image denoising and restoration, is a local feature of image-based recovery methods.
amfg07-demo-v1.tar
- This code implement method described in paper Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions
daisy-1.8.0.tar
- daisy local image feature
fingerprintverify
- 这是一个用C++语言实现一个指纹识别程序，要求满足FVC国际竞赛标准，并在学校建立的指纹库上实测。程序里应用到的技术有：中值滤波、直方图均衡化、脊线方向提取、Gabor滤波、指纹细化、特征提取、特征点过滤、基于局部特征点的特征匹配等等…… -This is a C++ language implementation with a fingerprint identification procedure that requires the FVC meet international com
Textureclassificationusingspectralhistograms
- Based on a local spatial/frequency representation,we employ a spectral histogram as a feature statistic for texture classification. The spectral histogram consists of marginal distributions of responses of a bank of filters and encodes implicit
ZhuoRanHIPS
- 病毒在计算机运行之后将根据自身的目的呈现出一系列的动作，包括写注册表项，生成文件，远程线程注入等等。本系统通过拦截系统调用对程序行为进行监控，将监控的行为信息交给监控中心和网络服务器分析处理，根据程序行为分析判断病毒，云安全概念的加入，本地特征库极小，占用系统资源很少。本系统设想根据这一系列的动作所组成的行为进行智能的逻辑判断该程序是不是病毒。-Will be followed by the virus in the computer is running according to their
ArteryReco
- 定性与定量地描述冠状动脉血管，很大程度依赖于造影图像中的血管结构识别结果，对此，提出了一种多特征模糊识别算法判别血管结构．实现过程中，首先通过图像预处理获得血管初始特征，然后利用一圆周探测器沿血管路径扫描并获取多种局部测度；在定义各种局部测度的多特征模糊子集及其隶属度函数之后，通过构造模糊识别算子准确地判别血管的端、段、分支和交叉结构．该方法在仿真血管模型和多套实际冠状动脉造影图像上获得了较好的效果，对实际图像的结构识别平均正确率达到92 。-Qualitative and quantitati
2
- 边缘特征的提取就是求图像梯度的局部最大值和方向。实际计算中，以微分算子的形式表示，并采用快速卷积函数来实现。常用的算子有微分算子，拉普拉斯算子，Canny算子等。其中Canny边缘检测是一种较新的边缘检测算子，具有较好的边缘检测性能，得到越来越广泛的应用。Canny边缘检测法利用高斯函数的一阶微分，它能在噪声抑制和边缘检测之间取得较好的平衡-Edge feature extraction is to seek the local maximum of image gradient and ori
Face_recognition
- 基于matlab的人脸识别分析，参考文献为： [1] X.Tan and B.Triggs. Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions, In Proceedings of the 2007 IEEE International Workshop on Analysis and Modeling of Faces and Gestures -Ma
Implementing-the-Scale-Invariant-Feature-Transfor
- The SIFT algorithm[1] takes an image and transforms it into a collection of local feature vectors. Each of these feature vectors is supposed to be distinctive and invariant to any scaling, rotation or translation of the image. In the original i
[16---2011]---local-binary-LDA-for-FaceR
- Extracting discriminatory features from images is a crucial task for biometric recognition. For this reason, we have developed a new method for the extraction of features from images that we have called local binary linear discriminant analysis (LB
local-features-research
- 基于局部特征的目标识别技术研究，阐述了解决遮挡情况下使用局部特征来识别目标的局部特征提取方法-Target recognition technology research based on local features of the local feature extraction methods solve occlusion using local feature to identify target