Description: 小波算法在vc的具体实现.小波算法在图像处理,视频压缩,特征提取等领域有广泛应用,程序以灰度图像为数据分别演示了一维和二维小波变换,希望对大家有所帮助.谢谢!-vc wavelet algorithm in a concrete realization. Wavelet algorithms in image processing, video compression, feature extraction and other fields have extensive application procedures to gray image data separately for a demonstration of 1D and 2D wavelet transform, we want to help. Thank you! Platform: |
Size: 173056 |
Author:朱江 |
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Description: 提出了一种新的基于小波过零检测的虹膜
识别算法,通过对分离的虹膜纹理采用小波变换来实现特征提取,最后通过Hamming距离完成模式匹配．-A new wavelet-based zero-crossing detection of the iris recognition algorithm, through the separation of the iris texture by wavelet transform to realize feature extraction, and finally through the Hamming distance from the completion of pattern matching. Platform: |
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Author:闫慧 |
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Description: 基于小波变换的三维模型提取技术的毕业论文,包括代码和答辩ppt.1．实现了三维模型的表示和规范化预处理过程，在此基础上，开发了进行检索实验的可视化特征提取实验平台。
2．结合球面调和变换获取旋转不变量具有降低特征向量维数的特性，实现了基于光线投射的特征提取方法，通过检索评价实验确定了参数的最佳取值。
3．分析了基本的光线投射方法和改进的光线投射方法的缺陷，提出了一种基于三维小波变换的特征描述方法。对光线投射算法进行了扩展，将切比雪夫采样点序列进行离散小波变换，然后利用球面调和变换获得旋转不变的特征向量。
4．将小波变换引入到体素表示的三维模型中，分别实现了表面体素小波变换和实体体素小波变换的特征提取，通过实验比较分析实体体素小波变换优于表面体素小波变换。
-Wavelet-Based Extraction of three-dimensional model of thesis, including the reply code and ppt.1. Three-dimensional model of the implementation and standardization of the express pre-treatment process, on this basis, developed a visual search experiment of feature extraction experiment platform.
2. Combination of spherical harmonic transform to obtain rotation invariant feature vector with reduced dimension of the characteristics of ray-casting based on the implementation of feature extraction methods, the evaluation by searching the parameters of the experiment to determine the best value.
3. Analysis of the basic ray casting method and the ray casting method to improve the shortcomings, a wavelet transform based on the three-dimensional characterization of the Ways. Ray-casting algorithm for the expansion of the sampling points Chebyshev sequences discrete wavelet transform, then the use of spherical harmonic transform to obtain rotation invariant feature vector.
4. Wavelet tr Platform: |
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Author:周光有 |
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Description: This paper identifies a novel feature space to
address the problem of human face recognition from
still images. This based on the PCA space of the
features extracted by a new multiresolution analysis
tool called Fast Discrete Curvelet Transform. Curvelet
Transform has better directional and edge
representation abilities than widely used wavelet
transform. Inspired by these attractive attributes of
curvelets, we introduce the idea of decomposing
images into its curvelet subbands and applying PCA
(Principal Component Analysis) on the selected
subbands in order to create a representative feature
set. Experiments have been designed for both single
and multiple training images per subject. A
comparative study with wavelet-based and traditional
PCA techniques is also presented. High accuracy rate
achieved by the proposed method for two well-known
databases indicates the potential of this curvelet based
feature extraction method.-This paper identifies a novel feature space to
address the problem of human face recognition from
still images. This is based on the PCA space of the
features extracted by a new multiresolution analysis
tool called Fast Discrete Curvelet Transform. Curvelet
Transform has better directional and edge
representation abilities than widely used wavelet
transform. Inspired by these attractive attributes of
curvelets, we introduce the idea of decomposing
images into its curvelet subbands and applying PCA
(Principal Component Analysis) on the selected
subbands in order to create a representative feature
set. Experiments have been designed for both single
and multiple training images per subject. A
comparative study with wavelet-based and traditional
PCA techniques is also presented. High accuracy rate
achieved by the proposed method for two well-known
databases indicates the potential of this curvelet based
feature extraction method. Platform: |
Size: 432128 |
Author:Swati |
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Description: 提出了基于特征融合和模糊核判别分析(FKDA)的面部表情识别方法。首先，从每幅人脸图像中手工定
位34个基准点，作为面部表情图像的几何特征，同时采用Gabor小波变换方法对每幅表情图像进行变换，并提取基
准点处的Gabor小波系数值作为表情图像的Gabor特征；其次，利用典型相关分析技术对几何特征和Gabor特征进
行特征融合，作为表情识别的输人特征；然后，利用模糊核判别分析方法进一步提取表情的鉴别特征；最后，采用最
近邻分类器完成表情的分类识别。通过在JAFFE国际表情数据库和Ekman“面部表情图片”数据库上的实验，证实
了所提方法的有效性。-Proposed based on feature fusion and fuzzy kernel discriminant analysis (FKDA) facial expression recognition. First, face images of each piece of hand-set
Bit 34 basis points, as the geometric features of facial expression images, while using Gabor wavelet transform method to transform the images of each piece of expression, and extraction-based
Quasi-point of the Gabor wavelet coefficients, as Gabor features of facial expression image second, using canonical correlation analysis on the geometric features and Gabor features into
Line feature fusion, as expression recognition of input features then, using fuzzy kernel discriminant analysis method to extract and further identification features of expression Finally, the most
Neighbor classifier to complete expression of the classification. International expression by JAFFE database and Ekman "facial image" database on the experiment, confirmed
The proposed method. Platform: |
Size: 375808 |
Author:MJ |
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Description: 小波变换是一种信号的时间—尺度分析方法，它具有多分辨率分析的
特点，而且在时频两域都具有表征信号局部特征的能力。由于其在信号处
理领域表现出的优异性能，目前在生物医学领域，广泛应用于信号检测、
特征提取、图像处理、信号压缩等方面。
-Wavelet transform is a signal of the time- scale analysis method, it has the characteristics of multi-resolution analysis, but also in time and frequency domain have the ability to characterize local signal characteristics. Signal processing because of its excellent performance shown by the current in the biomedical field, is widely used in signal detection, feature extraction, image processing, signal compression and so on. Platform: |
Size: 1928192 |
Author:Lily |
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Description: 将小波相邻系数相关性的降噪思想引入到冗余第2代小波中，提出了基于邻域相关性的冗余第2代小波降噪方法，该方法克服了传统阈值降噪没有考虑小波系数之间相关性的不足。-Aiming at fault feature extraction in the background of strong noise, a wavelet denoising idea by incorporating neighboring coefficients is introduced into redundant second generation wavelet case. A denoising method of redundant second generation wavelet using neighbor dependency is presented. It overcomes the deficiency of traditional thresholding approaches. In this method, an original signal is decomposed by redundant second generation wavelet, and the detail and approximation signals have the same length as the original signal. The detail signals at each scale are then processed by neighbor dependency. Finally, the approximation signal and processed detail signals are reconstructed by inverse transform of redundant second generation wavelet to realize the signal denoising. Platform: |
Size: 7168 |
Author:杨飞宇 |
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Description: 首先，仿真信号建模；其次，形态学滤波及小波方法滤波；最后，特征提取-First, the simulated signal modeling followed by morphological filtering and wavelet filtering Finally, the feature extraction Platform: |
Size: 57344 |
Author:houzhoubo |
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Description: 文中从小波变换的角度出发,通过在尺
度域上对信号能量的一种划分,引入了小波能谱与小波熵作为信号特征提取的特征量来反映系统信号的统计特征。实验结果表明,该算法能有效提取弹丸激波信号特征,速度快、准确率高,而且具有对噪声不敏感的优势。
-Paper, starting from the point of view of the wavelet transform, introduced by a division of the signal energy scale domain, wavelet energy spectrum and wavelet entropy feature as a signal feature extraction amount to reflect the statistical characteristics of the system signals. The experimental results show that the algorithm can effectively extract the the projectile shock signal characteristics, speed, high accuracy, and is not sensitive to noise advantage. Platform: |
Size: 167936 |
Author:陶伟 |
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Description: 通过小波变换对少量样本进行特征提取，达到识别同类物体的效果。-Of a small sample of feature extraction by wavelet transform, to achieve the effect of the recognition of similar objects. Platform: |
Size: 78848 |
Author:李 |
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Description: 小波分析可同时从时域和频域两个方面对信号进行分析，结合包络分析十分适合滚动轴承的故障特征提取；基于双通道的全矢小波分析方法不仅对单通道小波分析方法具有兼容性，而且弥补了传统的基于单通道信
息进行旋转机械故障特征提取造成的信息量不完整、易导致误诊的弊端。结果表明，在针对滚动轴承外圈故障特征提取时，全矢小波分析方法较小波一包络分析方法具有一定的优势。 -Wavelet analysis simultaneously from the time domain and frequency domain analysis of two aspects of the signal, combined envelope analysis is very suitable for roller bearing fault feature extraction based on a dual-channel full vector wavelet analysis method is not only right channel wavelet analysis method has compatibility, And make up the traditional channel-based information extraction rotating machinery fault caused by the amount of information is not complete, easily lead to misdiagnosis of the state. The results show that for the outer bearing fault feature extraction, wavelet analysis method full vector wave a smaller envelope analysis method has certain advantages. Platform: |
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Author:张力 |
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Description: Colourhistogram
II. TEXTURE FEATURE EXTRACTION IN CBIR
An overview of the proposed CBIR system is illustrated
in Fig. 1. The proposed algorithm, Label Wavelet Transform
(LWT), is based on color image segmentation [1], and it is
an extension of DWT-based texture feature extraction method.
The 2-D DWT is computed by applying separable filter banks
to the gray level images. The detail images Dn,1, Dn,2,
and Dn,3 are obtained by band-pass filtering in a specific
direction, and they can be categorized into three frequency
bands: HL, LH, HH band, respectively. Each band contains
different directional information at scale n. The texture feature
is extracted from the variance (ó2
n,i) of the coefficients cn,i of
the detail image Dn,1, Dn,2, and Dn,3 at different scale n.To
represent the texture feature of an image q, the texture feature
vector of DWT is defined as [2]:
TDWT (q) = [ó2
1,1, ó2
1,2, ó2
1,3, ..., ó2N
max,3], (1)
where Nmax denotes the largest scale. In this work, Nmax Platform: |
Size: 1024 |
Author:lavanya |
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Description: Content-Based Image Retri (CBIR) allows to
automatically extracting target images according to objective
visual contents of the image itself. Representation of visual
eatures and similarity match are important issues in CBIR. In
his paper a novel CBIR method is proposed by exploit the
wavelets which represent the visual feature. We use Haar and
D4 wavelet to decompose color images into multilevel scale and
wavelet coefficients, with which we perform image feature
extraction and similarity match by means of F-norm theory.
Furthermore, we also provide a progressive image retri
strategy to achieve flexible CBIR. We tested five categories of
color images in the experiments. The retri performance of
D4 and Haar wavelet is compared with wavelet histograms in
erms of recall rate and retri speed. Experiment results
reflect the importance of wavelets in CBIR and F-norm theory
along with progressive retri strategy achieves efficient
retri . -Content-Based Image Retri (CBIR) allows to
automatically extracting target images according to objective
visual contents of the image itself. Representation of visual
eatures and similarity match are important issues in CBIR. In
his paper a novel CBIR method is proposed by exploit the
wavelets which represent the visual feature. We use Haar and
D4 wavelet to decompose color images into multilevel scale and
wavelet coefficients, with which we perform image feature
extraction and similarity match by means of F-norm theory.
Furthermore, we also provide a progressive image retri
strategy to achieve flexible CBIR. We tested five categories of
color images in the experiments. The retri performance of
D4 and Haar wavelet is compared with wavelet histograms in
erms of recall rate and retri speed. Experiment results
reflect the importance of wavelets in CBIR and F-norm theory
along with progressive retri strategy achieves efficient
retri . Platform: |
Size: 2514944 |
Author:santhosh d |
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Description: 通过matlab代码，滤波求和方式实现宽带波束形成，感应双馈发电机系统的仿真，用于信号特征提取、信号消噪，直线阵采用切比学夫加权控制主旁瓣比，有小波分析的盲信号处理。-By matlab code, Filtering summation way broadband beamforming, Simulation of doubly fed induction generator system, For feature extraction, signal de-noising, Linear array using cut than learning laid upon the right control of the main sidelobe ratio, There Wavelet Analysis Blind Signal Processing. Platform: |
Size: 8192 |
Author:xiswkk |
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Description: matlab小波分析程序，采用波束成形技术的BER计算，可以得到很精确的幅值、频率、相位估计，用于信号特征提取、信号消噪，实现了对10个数字音的识别。-matlab wavelet analysis program, By applying the beam forming technology of BER You can get a very accurate amplitude, frequency, phase estimation, For feature extraction, signal de-noising, To achieve the recognition of 10 digital sound. Platform: |
Size: 6144 |
Author:nfzeka |
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Description: 包括AHP，因子分析，回归分析，聚类分析，用于信号特征提取、信号消噪，课程设计时编写的matlab程序代码，借鉴了主成分分析算法（PCA），关于小波的matlab复合分析，通过matlab代码，采用加权网络中节点强度和权重都是幂率分布的模型，虚拟力的无线传感网络覆盖。- Including AHP, factor analysis, regression analysis, cluster analysis, For feature extraction, signal de-noising, Course designed to prepare the matlab program code, It draws on principal component analysis algorithm (PCA), Matlab wavelet analysis on complex, By matlab code, Using weighted model nodes in the network strength and weight are power law distribution, Virtual power wireless sensor network coverage. Platform: |
Size: 6144 |
Author:essvu |
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Search - feature extraction by wavelet