Description: The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented.-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all the data, coming from the different modalities, are displayed in proper locations. The term image registration is most commonly used to denote the process of alignment of images , that is of transforming them to the common coordinate system. This is done by optimizing a similarity measure between the two images. A widely used measure is Mutual Information (MI). This method requires estimating joint histogram of the two images. Experiments are presented that demonstrate the approach. The technique is intensity-based rather than feature-based. As a comparative assessment the performance based on normalized mutual information and cross correlation as metric have also been presented. Platform: |
Size: 98304 |
Author:Harry |
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Description: 提出一种新的非线性变换的彩色空间 ″″, 利用次高斯概率分布函数拟合皮肤色度信息, 得到候选区
YC C
r b
域。为了排除候选区域中的非人脸, 首先根据均值和方差信息分割出候选区域中的纹理特征信息, 再通过多尺度
)
(
信息定位眼睛, 然后根据人脸特征的几
形态边缘检测算子检测候选区域的边缘, 利用 边缘方向
PCA PCAED
( )
何形状信息定位其他特征 鼻、嘴 , 通过这些几何特征信息对肤色分割得到的候选区域进行验证, 最终得到正确
的人脸区域。利用3 个实验数据集测试该算法, 并与其它相应的算法相比较, 提出的非线性彩色空间对于肤色分
割具有很好的效果, 且对光照和姿态具有良好的不变性。另外, 利用 信息和几何特征信息检测人脸特征
PCAED
具有很高的定位精度, 定位检测率优于其他方法。实验结果表明, 该算法具有定位准确率高, 漏检率和误检率低
等特点。-
A novel approach for skin segmentation and facial feature extraction is proposed
The proposed skin segmentation is a method for integrating the chrominance components of
″″ . ″″
r b r b
nonlinear YC C color model The chrominance components of nonlinear YC C color space
,
are modeled using a subgaussian probability density function and then the face skin is seg
. ,
mented based on this function In order to authenticate the face candidate regions firstly tex
ture information in face candidate regions is segmented using mean and variance of luminance
, . ,
information and then the eye is located by the PCA edge direction information Finally the
, ,
others features such as nose and mouth also are detected using the geometrical shape infor
. 2 ,
mation As all the above mentioned techniques are simple and efficient the skin segmentation
.
based on nonlinear color spacemethod has the invariability of lighting and pose In the experi
, .
ments themethod has been successfull Platform: |
Size: 458752 |
Author:zz |
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Description: A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects,
is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel. The
masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem
can be formulated using the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya coefficient as
similarity measure, and use the mean shift procedure to perform the optimization. In the presented tracking examples, the new method
successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data
association techniques is also discussed. We describe only a few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking. Platform: |
Size: 2459648 |
Author:Ali |
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Description: 摘 要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不
适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并,
对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的
舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。-Tongue’ s crack is a very important part of herbalist doctor diagnosis. For the different screen conditions , there are many differ2
ences on the tongue’ s quality. It is not effective to use the t raditional threshold ext raction algorithm. In order to solve this problem , pro2
pose a new adaptive threshold algorithm. Present the segmentation of the image of tongue by using the feature on tongue in the L 3 a 3
b color space and the split- combining algorithm. Then use the threshold , which is the color value ext racted automatically in the middle
of the tongue , to detect the crack of the whole tongue. The experiments show that this approach is able to distill the crack effectively to
different tongue images , and achieve the objectivity of the diagnosis based on the tongue’ s crack. Platform: |
Size: 604160 |
Author:christine |
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Description: function Invariant_Line_Feature_Matching
___DESCRIPTION___
Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? )
Example :
Invariant_Line_Feature_Matching ( )
___REFERENCE___
Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach
Park, Lee, Lee - Ideal - CV and Im. Und. - 77, 263-283 - (2000)- function Invariant_Line_Feature_Matching
___DESCRIPTION___
Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? )
Example :
Invariant_Line_Feature_Matching ( )
___REFERENCE___
Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach
Park, Lee, Lee- Ideal- CV and Im. Und.- 77, 263-283- (2000) Platform: |
Size: 27648 |
Author:Mehmet |
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Description: 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 introduced by
using the SVM. The kernel mapping idea is used to derive the
non-linear version, Kernel Discriminant via Support Vectors (SVKD).
In SVDA, only support vectors are involved to obtain the
transformation matrix. Thus, the computational complexity can be
greatly reduced for kernel based feature extraction. Experiments
carried out on several standard databases show a clear improvement
on LDA-based recognition Platform: |
Size: 2048 |
Author:sofi |
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Description: sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper:
Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fuzzy Rules with Reduced Attributes for the Monitoring of Complex Systems. Engineering Applications of Artificial Intelligence, 13(3):263-278, 2000.
rsar reads in a MIMO (Multiple Input, Multiple Output) dataset, performs RS-based feature selection on it, and returns the selected feature subset.
Four versions of the QuickReduct algorithm are supported, QuickReduct, QuickReduct III, QuickReduct IV and QuickReduct V (progressively faster implementations). QuickReduct II is a backward elimination version of QuickReduct and is not supported yet neither is exhaustive search for reducts. -sar is a Rough Set-based Attribute Reduction (aka Feature Selection) implementation. This is an implementation of ideas described, among other places, in the following paper:
Qiang Shen and Alexios Chouchoulas, A Modular Approach to Generating Fuzzy Rules with Reduced Attributes for the Monitoring of Complex Systems. Engineering Applications of Artificial Intelligence, 13(3):263-278, 2000.
rsar reads in a MIMO (Multiple Input, Multiple Output) dataset, performs RS-based feature selection on it, and returns the selected feature subset.
Four versions of the QuickReduct algorithm are supported, QuickReduct, QuickReduct III, QuickReduct IV and QuickReduct V (progressively faster implementations). QuickReduct II is a backward elimination version of QuickReduct and is not supported yet neither is exhaustive search for reducts. Platform: |
Size: 730112 |
Author:NH |
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Description: matching shape can be subdivided between two approaches: feature-based and template-based matching. The feature-based approach uses the features of the search and template image, such as edges or corners, as the primary match-measuring metrics to find the best matching location of the template in the source image. The template-based, or global, approach, uses the entire template, with generally a sum-comparing metric (using SAD, SSD, cross-correlation, etc.) that determines the best location by testing all or a sample of the viable test locations within the search image that the template image may match up to. Platform: |
Size: 10481664 |
Author:gislam |
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Description: his a simple method for silence removal and segmentation of audio streams that contain speech. The method is based in two simple audio features (signal energy and spectral centroid). As long as the feature sequences are extracted, as thresholding approach is applied on those sequence, in order to detect the speech segment-his is a simple method for silence removal and segmentation of audio streams that contain speech. The method is based in two simple audio features (signal energy and spectral centroid). As long as the feature sequences are extracted, as thresholding approach is applied on those sequence, in order to detect the speech segment Platform: |
Size: 980992 |
Author:petr |
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Description: paper about Feature selection and parameter optimization for support vector machines:
A new approach based on genetic algorithm with feature chromosomes Platform: |
Size: 861184 |
Author:mar |
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Description: 对特征选择方法的发展历史和现状进行了跨学科的广泛调研，在此基础上总结提出了通用的方法定义和算法流程框架-A unifring approach to the definition of the feature selection problem and corresponding algorithm design framework are proposed based on a complete survey
of a wide range of interdisciplinary research Platform: |
Size: 913408 |
Author:刘建飞 |
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Description: Support Vector Machines, one of the new techniques for pattern classifi cation, have been widely used in many application areas. The kernel
parameters setting for SVM in a training process impacts on the classifi cation accuracy. Feature selection is another factor that impacts
classifi cation accuracy. The objective of this research is to simultaneously optimize the parameters and feature subset without degrading the SVM
classifi cation accuracy. We present a genetic algorithm approach for feature selection and parameters optimization to solve this kind of problem. Platform: |
Size: 141312 |
Author:payal |
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Description: 为提高基于内容的图像检索系统中纹理特征提取的有效性,提出了又一种纹理图像检索方法。该方法
利用非下采样 Contourlet变换对图像进行分解, 提取不同子带和不同方向变换系数矩阵的均值和方差为特征向量, 作
为数据库中纹理图像的索引,并利用两种不同的相似度函数计算图像之间的相似度,建立了一套基于示例查询图像
的纹理图像检索系统。实验结果表明,与小波包等特征提取方法相比, 该方法不仅能降低特征向量维数,而且能取得
更高的检索准确率和检索速度。-To i ncrease t he vali d ity o f tex t ure feature ex tracti on in conten t-based i mage retrieva l syste m, a nove l approach
for tex ture i m age retr ieva lw as proposed . Th i s approach w as based on theNonSubsamp l ed Con t our l et T ransform ( NSCT). The
m eans and variab l es of NSCT co efficien tsm a trix i n d ifferen t s ubbands and var i ous directi ons were ex tracted to for m the feature
vectors wh ich we re reg arded as i ndexes of tex t ure i mages i n i m age da tabase . Two s i m il ar ity functi ons were used to compute the
si m ilar i ty bet w een i m ages . A tex ture re trieval sy stem based on query i m age w as deve l oped . Co m pared to the w ave let packag e
transform, th i s approach can no t on l y reduce the di m ension o f feature vectors , but a l so get higher accu racy and speed of
retr i eva. l Platform: |
Size: 346112 |
Author:jjdjjf |
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Description: Two novel contributions to Content Based Image Retrieval are presented and
discussed. The fi rst is a search engine for font recognition. The intended usage
is the search in very large font databases. The input to the search engine is an
image of a text line, and the output is the name of the font used when printing
the text. After pre-processing and segmentation of the input image, a local
approach is used, where features are calculated for individual characters. The
method is based on eigenimages calculated from edge fi ltered character images,
which enables compact feature vectors that can be computed rapidly. A system
for visualizing the entire font database is also proposed. Applying geometry
preserving linear- and non-linear manifold learning methods, the structure of
the high-dimensional feature space is mapped to a two-dimensional representa-
tion, which can be reorganized into a grid-based display. Platform: |
Size: 455680 |
Author:Chandana |
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Description: This a Independent component approach face recognition matlab file of the feature-based approach.-This is a Independent component approach face recognition matlab file of the feature-based approach. Platform: |
Size: 3072 |
Author:free_me4liv |
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Description: 本文提出一种通过实时调整目标特征权值来进行背景自适应跟踪的算法。首先，定义了一种综合特征集合用以描述目标的颜色和局部轮廓。其次，提出了在滤波框架中对目标特征进行评估的算法，从而使得具有强区分能力的特征占有较大的权值，进而使其能够在跟踪过程起到较大的作用。采用传统的Kalman 滤波和粒子滤波对所提出的算法进行了验证。-In this paper, we propose a new adaptive visual object tracking method based on
online feature evaluation approach. First, a feature set is built by combining color
histogram (HC) with gradient orientation histogram (HOG), which emphasizes both
color and contour representation. Then a feature confidence evaluation approach is
proposed to make features with higher confidences play more important roles in the
instantaneous tracking ensuring that the tracking can adapt to the appearance change
of both the object and its background. The feature evaluation approach is fused with
filter frameworks, e.g. Kalman and Particle filter, to keep the temporal consistency of feature confidence evolution. Platform: |
Size: 1602560 |
Author:wenping |
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Description: A digital image watermarking scheme must be robust against a
variety of possible attacks. In the proposed approach, a new
rotation and scaling invariant image watermarking scheme is
proposed based on rotation invariant feature and image
normalization. The rotation invariant features are extracted
from the segmented areas and are selected as reference points.
Sub-regions centered at the feature points are used for
watermark embedding and extraction. Image normalization is
applied to the sub-regions to achieve scaling invariance. In the
scheme, first, the image is segmented into a number of
homogeneous regions and the feature points are extracted. Then
the circular regions for watermark embedding or extraction are
defined. Based on the image normalization and orientation
assignment, the rotation, scaling, and translation invariant
regions can be used for watermark embedding and extraction. Platform: |
Size: 1475584 |
Author:prasannakumar |
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Description: This paper presents a rule-based approach for the classification of power quality disturbances. The
disturbed signal is first characterized using the multi-resolution S-transform, which acts as a feature
extraction tool. Then, a simple but robust rule-based classification algorithm is used to identify disturbances.-This paper presents a rule-based approach for the classification of power quality disturbances. The
disturbed signal is first characterized using the multi-resolution S-transform, which acts as a feature
extraction tool. Then, a simple but robust rule-based classification algorithm is used to identify disturbances.
Platform: |
Size: 1021952 |
Author:s |
Hits:
Search - Feature based Approach