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OPENCV写的一个小程序
- OPENCV写的一个小程序 包括将彩色图片转成灰度图以及做阈值分割和主成分分析的功能-OPENCV write a small program, including a color picture converted to grayscale and make thresholding and principal component analysis of functional
pca
- 用开源软件R实现的主成成分分析pca程序。-Using open source software to achieve the main R into components analysis PCA procedures.
matlab
- ) 使用分块的主成分分析方法(PCA)对人脸图像进行压缩编码。针对PCA方法计算量大的缺点,首先把问题转化成奇异值分解(SVD)问题,然后设计了特征空间的更新算法,通过递推,简化每一步计算的计算量,达到了实时编码的要求。 4) 在Windows平台下基于Video for Windows(VFW)接口开发了人脸视频图像编码和解码的实验系统,该系统实现了图像采集、图像显示、编码、解码等功能。-) The use of sub-blocks of principal component analys
PCA_based-Face-Recognition-System
- 利用主成成分分析PCA对指定图片进行识别。附带测试图片，适合初学者。-Component of the principal component analysis PCA to identify the specified picture. Incidentally test images, suitable for beginners.
2DPCA
- 2DPCA,即二维主成分分析，相对于传统的PCA（主成分分析），2DPCA在对二维图像进行降维时不需要转成一维（向量）-2DPCA, ie two-dimensional principal component analysis, as opposed to the traditional PCA (Principal Component Analysis), 2DPCA in dimensionality reduction of two-dimensional images into one
tPCA-for-MA-removal-in-fNIRS
- 在脑功能近红外光谱成像中基于伪迹检测的主成分分析运动伪迹移除方法(靶向主成分分析去噪方法)-In brain functional near-infrared spectroscopic imaging, motion artifact removal method based on motion artifact detection PCA(targeted principal component analysis denoising method)
pca
- 利用OpenCV库函数实现PCA（主成成分分析）算法，该算法是经典人脸识别算法Eigenface里的核心算法。-Use OpenCV library functions achieve PCA (Principal Component Analysis into) algorithm, which is a classic face recognition algorithm Eigenface in core algorithm.