Search - DCT face

[Special Effects] DCT2DPCA

Description: 基于对角DCT和2Dpca的matlab人脸识别源码。-right angle based on DCT and the Matlab 2Dpca Face Recognition source.
Platform: | Size: 2048 | Author: 文滔 | Hits:

[Mathimatics-Numerical algorithms] DCT

Description: 用DCT进行人脸识别，用MATLAB实现-Using DCT for Face Recognition using MATLAB realize
Platform: | Size: 76800 | Author: 李晋博 | Hits:

Description: dct二维离散余弦变换里面采用了经典的美人人脸识别图片，为自动加载，用DCT法后能统计使用时间，也用了FDCT法，明显速度优于DCT.-two-dimensional discrete cosine transform DCT inside a classic beauty face recognition picture, in order to automatically load, using DCT method to use after the statistical time spent FDCT law, obviously the speed is better than DCT.
Platform: | Size: 128000 | Author: 沧海客 | Hits:

[hospital software system] fdv41

Description: 人脸检测，基于gabor的提取特征，利用人工神经网络进行人脸检测-Face detection, based on the extraction of gabor features, the use of artificial neural networks Face Detection
Platform: | Size: 15401984 | Author: smallbearpapa | Hits:

[AI-NN-PR] face_recognition

Description: 基于2D-DCT和模块2DPCA的人脸识别系统的实现（matlab）
Platform: | Size: 2057216 | Author: da | Hits:

[Graph program] FaceRecognition

Description: 这是一个用matlab做的人脸识别系统，里面包含了几十张人脸数据图像，值得一荐-This is a matlab to do with Face Recognition System, which contains dozens of Zhang Face image data, it is worth sacral
Platform: | Size: 305152 | Author: 鄙人不善奔跑 | Hits:

[Graph Recognize] faceRecognition

Description: 基于2D-DCT和模块2DPCA的人脸识别系统的实现（matlab）-Based on the 2D-DCT and modules 2DPCA Face Recognition System (matlab)
Platform: | Size: 4164608 | Author: 黄文 | Hits:

[Graph program] 61EDA_C1600

Description: 人脸识别，基于2D的PCA结合2D的DCT分块-face recognition ,based 2DPCA and 2DDCT
Platform: | Size: 2059264 | Author: lily | Hits:

[Graph program] DWT_DCT

Description: 与可见光图像不同的是，这是一个红外人脸识别的DWT+DCT算法-And visible light images, this is an infrared face recognition algorithm of DWT+ DCT
Platform: | Size: 2048 | Author: Louis lu | Hits:

[Special Effects] A_Study_og_Face_Recognition_Methods_Baced_on_Wavel

Description: 针对灰度图像，提出一种基于知识的人脸检测方法。提出了一种给予支持向量机的人脸检测方法。提出了一种基于小波分解的LDA人脸识别方法。提出了一种基于小波和DCT的人脸识别方法。提出了一种机遇CEDT和支持向量机的人脸分类和识别方法。 -For gray-scale images, a knowledge-based face detection methods. A support vector machine method of face detection. A wavelet decomposition of the LDA-based face recognition methods. A wavelet and DCT-based face recognition methods. A CEDT opportunities and support vector machine classification and face recognition.
Platform: | Size: 7113728 | Author: yanyan | Hits:

[Speech/Voice recognition/combine] DisCosTrans

Description: face recognition using DCT
Platform: | Size: 361472 | Author: naouar | Hits:

[matlab] ar_dct_kda

Description: 在AR人脸库上进行DCT变换，使用DCT变换后的图像进行 kernel fisher discriminant analysis,其中kernel 函数可以自己选择-In the AR face database on the DCT transform, using the DCT transformed image kernel fisher discriminant analysis, which can choose the kernel function
Platform: | Size: 2048 | Author: 邵珠立 | Hits:

[matlab] ar_dct_lda

Description: 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.
Platform: | Size: 2048 | Author: 邵珠立 | Hits:

[AI-NN-PR] DCT

Description: 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BP神经网络分类器，同时采用BP神经网络分类器作为本次基于DCT的人脸识别系统设计的分类器，并对BP神经网络进行分类的算法进行设计，BP神经网络具有学习功能，只要采用本系统对训练图片进行训练，就可以记下图像的相关信息，对于测试图片，就可以很准确的识别出该图片是属于哪个的。最后，本文对整个人脸识别系统设计实验进行了实验分析，实验结果表明本文采用的方法切实有效。- This is the design of the DCT-based face recognition systems. First of all, the background light of the current face recognition and face recognition to discuss the development of research in all aspects of content and applications And then studied the pretreatment of face recognition to discuss the pre-treatment of other face recognition methods,and analysis of the pros and cons of various methods, finally, the use of DCT (discrete cosine transform) image pre-processing to achieve in the face of the reduced-order processing Next on the face image feature extraction have been studied, A brief description of the feature extraction and algebraic geometry feature extraction, while in-depth study based on the DCT and the PCA Transform face image feature extraction in order to achieve face recognition system to identify whether the rate of increase in the research For the choice of classifier, this paper carried out on two of classifier, that is, nearest neighbor classifier and BP neura
Platform: | Size: 422912 | Author: 刘文珍 | Hits:

[Other] IFI_DB

Description: face recognition using dct and neural networks
Platform: | Size: 2386944 | Author: salma | Hits:

[Wavelet] faceregreport

Description: This document describe the face regenition system using DCT and fisher algorithm based efficent metohd for face regnition system.
Platform: | Size: 777216 | Author: Selvakumar | Hits:

[Graph Recognize] dctannprotected

Description: High information redundancy and correlation in face images result in efficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.-High information redundancy and correlation in face images result in inefficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.
Platform: | Size: 25600 | Author: mhm | Hits:

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