搜索资源列表
ar_dct_lda
- AR人脸库进行DCT变换，然后使用Fisher discriminant analysis 进行特征提取，使用cos分类器进行人脸分类。-AR Face Database for DCT transform, and then use the Fisher discriminant analysis feature extraction, using cos classifier for human face classification.
RELAX
- RELLAX算法，特征提取，目标识别，很好的资料！-RELLAX algorithm, feature extraction, object recognition, very good information!
FeaturesSkeleton
- feature extraction and matching algorithm
Medical-Image-Matching.ashx
- 用matlab编写的用于医学图像。很实用。大家可以参考参考。-Using matlab to prepare for the license plates feature extraction. Very practical. Members can refer to reference
Feature-based_face_detection_system
- 基于特征的人脸检测系统的设计与实现,是用opencv的haartraining库-Feature-based face detection system design and implementation, is to use opencv library in haartraining
DCT
- 本文设计基于DCT的人脸识别系统，首先结合当今人脸识别的背景和发展状况讨论了人脸识别的研究内容及在各方面的应用；然后研究了人脸识别进行预处理，讨论了人脸识别预处理的其他方法，分析各种方法的利弊，最后采用DCT（离散余弦变换）实现人脸图像预处理中的降维处理；接下来对人脸图像的特征提取进行了研究，简单叙述了几何特征提取和代数特征提取，同时深入研究了基于DCT和PCA变换的人脸图像特征提取，从而实现是否对人脸识别系统识别率有所提高的研究；对于分类器的选择，本文对两种分类器进行了探讨，即最近邻分类器和B
SIFT
- SIFT特征提取演算法(包含匹配以及除错机制RANSAC)-可用于两张影像之特征点匹配 -SIFT feature extraction algorithm (including the match, as well as debug mechanisms RANSAC)- can be used for two images of the feature points matching
face
- 人脸识别程序，采用的是knn分类器，基于类内类间距离准则，特征提取。-Face recognition process, using the knn classifier, based on within-class inter-class distance criteria, feature extraction.
MPCALDA
- 编程是由pca和lda结合的脸部特征提取，用于三维图像。-multilinear principal component analysis combined with Linear discriminant analysis 3D face feature extraction.
07ICIPShi
- 图像特征隐写分析，用于分析图像是否含有秘密信息-Image feature steganalysis for the analysis of the image if it contains confidential information
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
anp
- NP是美国匹兹堡大学的T.L.Saaty 教授于1996年提出了一种适应非独立的递阶层次结构的决策方法，它是在网络分析法（AHP）基础上发展而形成的一种新的实用决策方法。其关键步骤有以下几个： 1 确定因素，并建立网络层和控制层模型。 2 创建比较矩阵。 3 按照指标类型针对每列进行规范化。 4 求出每个比较矩阵的最大特征值和对应的特征向量。 5 一致性检验。如果不满足，则调整相应的比较矩阵中的元素。 6 将各个特征向量单位化(归一化)
3d-matching
- 提出了一种用于物体外形非接触式提取的综合立体匹配方法。该方法综合了基于面积的立体匹配过程和基于特征的立体匹配过程。能充分利用它们各自的优点。 既能产生致密视差图。又能获得不连续处的准确匹配。 解决了物体外形非接触式提取中的关键性的问题实验结果以及实际应用都收到了很好的效果。-Proposed for object shape extraction of non-contact integrated stereo matching method. This method is an integra
examples-code
- 由ＵIUC的Yi Ma开发的关于多视觉几何理论的开发包。其中涉及到特征点提取，光流，分层重建理论。一步一步教你如何构建一个重建的系统-developed by Yi Ma from UIUC Which involves the feature point extraction, optical flow, layered reconstruction of the theory. Step by step teach you how to build a reconstruction syst
SVM
- In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is in
lda
- lda线性特征提取，用于人脸识别，首先进行小波特征提取后用lda提取特征。-lda linear feature extraction for face recognition, first of all, after feature extraction using wavelet feature extraction using lda.
phoneme_feature-mr4-rel-src-b01-20_apr_2009
- phoneME feature MR4(最新版)源码-phoneME feature MR4 (latest version) source code
Alaa_Box_sent
- This toolBox used in the image processing(feature extraction and classification)
extractFeatures
- These source codes are for image feature extraction in Matlab
autoCornerFinder_win
- 自动的角点检测算法。运用SIFT特征，对图像中的特征点进行提取！试过，好用！-Automatic corner detection algorithm. The use of SIFT features, right in the image feature point extraction! Tried, easy to use!