Description: 对由光源颜色变化引起的图像色彩偏差,进行了校正,并在YCbCr颜色空间建立了Cb-Cr色度查找表和亮度信息联合的肤色模型,应用预处理技术,去除部分非人脸区域,减少人脸检测的搜索空间,并采用模板匹配方法在人脸候选区域检测人脸.实验表明,该方法能够有效的从复杂环境的彩色图像中检测出左右旋转不超过45°的人脸,且不受人脸表情、尺度和数目的影响,且错误率较低.-Color by the light source caused by the change of image color deviation, a correction, and YCbCr color space established a Cb-Cr chrominance and luminance information look-up table of the color model of the joint application of pre-treatment technology, to remove some non-human face region, Face detection to reduce the search space, using a template matching method in the face candidate region detection of human faces. experiments show that the method can be effective in complex environments from color images detected no more than about 45 ° rotation of the human face, and from Facial Expression, scale and number of impact, and lower error rate. Platform: |
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Author:lll |
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Description: We propose an algorithm for facial expression recognition which can classify the given image into one of the seven basic facial expression categories (happiness, sadness, fear, surprise, anger, disgust and neutral). PCA is used for dimensionality reduction in input data while retaining those characteristics of the data set that contribute most to its variance, by keeping lower-order principal components and ignoring higher-order ones. Such low-order components contain the "most important" aspects of the data. The extracted feature vectors in the reduced space are used to train the supervised Neural Network classifier. This approach results extremely powerful because it does not require the detection of any reference point or node grid. The proposed method is fast and can be used for real-time applications. Platform: |
Size: 21504 |
Author:mhm |
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Description: One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Transform with Perceptron Neural Network.. and the other based on Discrete Cosine Transform with Perceptron Neural Network ...
2- In face expression recognition .. we defined the condition of the person (nature,happiness,disgust or anger)
this source code is based on Principle component analysis(PCA) ..
* we need to now about digital image processing
,neural network and PCA-One of Biometrics fields is face recognition & face expression recognition ...
1- In face recognition .. we need to design authentication program by training a neural network ,there are two source codes..one of them is based on Discrete Wavelet Transform with Perceptron Neural Network.. and the other based on Discrete Cosine Transform with Perceptron Neural Network ...
2- In face expression recognition .. we defined the condition of the person (nature,happiness,disgust or anger)
this source code is based on Principle component analysis(PCA) ..
* we need to now about digital image processing
,neural network and PCA... Platform: |
Size: 11905024 |
Author:mahmoud |
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Description: RNA 和 DNA序列模拟 基因建模 数值模拟 采用matlab 编写 能计算几千个 基因点的特性和行为-In one type of gene expression analysis, fluorescently tagged messenger RNA from different cells are hybridized to a microscopic array of thousands of complimentary DNA spots that correspond to different genes. Illuminated spots emit different color light, indicating which genes are expressed (e.g., green=control, red=sample, yellow=both).
In this case study, MATLAB, the Image Processing and Signal Processing toolboxes were used to determine the green intensities from a small portion of a microarray image containing 4,800 spots. A 10x10 pattern of spots was detected by averaging rows and columns to produce horizontal and vertical profiles. Periodicity was determined automatically by autocorrelation and used to form an optimal length filter for morphological background removal. A rectangular grid of bounding boxes was defined. Each spot was individually addressed and segmented by thresholding to form a mask. The mask was used to isolate each spot from surrounding background. Individu Platform: |
Size: 4450304 |
Author:Tu Shu |
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Description: Matlab表情识别，特征脸[1 ]作为面部表情分类的方法。首先，利用训练图像创建低维人脸空间（pca）。这是通过训练图像集主成分分析（PCA）及图片主成分分析（即具有较大特征值的特征向量）获得的。
结果，所有的测试图像以所选择的主成分表示，计算投影图像与所有投影列车图像的欧几里得距离，选择最小值以找出与试验图像最相似的训练图像。(The feature face [1] is used as a facial expression classification method. Firstly, a low-dimensional face space (pca) is created using training images. This is obtained by training principal component analysis (PCA) of image set and principal component analysis of image (i.e. eigenvectors with larger eigenvalues).
As a result, all the test images are represented by the selected principal components, the Euclidean distance between the projected image and all the projected train images is calculated, and the minimum value is selected to find the training image most similar to the test image.) Platform: |
Size: 4684800 |
Author:bbqQq |
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Search - image expression by matlab