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zhifangtu_code
- 用matlab函数实现给定图像的直方图;函数histeq()实现直方图均衡化;对给定图像,各自指定直方图,进行直方图匹配,使图像增强。这是个模板-Implemented by matlab function to a given image histogram function histeq () to achieve histogram equalization for a given image, each designated histogram, histogram matching
siftDemoV4
- sift算法在图像匹配领域有着重要作用,通过sift算法可以将模板图片和待检测图片进行特征点提取并进行匹配。-sift algorithm has an important role in the field of image matching, sift algorithm by template image and image to be detected can be the feature point extraction and matching.
correlation
- 给定待匹配图像和模板图像,基于SSD和Correlation对图像进行匹配。-matching based on correlation
Matching
- 基于Halcon 与C#实现匹配功能,实现创建模板,优化,查找-Based Halcon and C# matching is performed to create a template, optimization, find
DaXia
- 图像处理的一些简单应用,包括模板创建,匹配等,大虾实验室。-DaXia laboratory
ivsphwsj
- 实现了对10个数字音的识别程序WQAxfHV参数粒子图像分割及匹配均为自行编制的子例程,是一种双隐层反向传播神经网络,包含位置式PID算法、积分分离式PID,fxcBAHK条件在matlab R2009b调试通过,通过反复训练模板能有较高的识别率。- Realization of 10 digital audio recognition program WQAxfHV parameter Particle image segmentation and matching subroutines
tjdigxae
- 有详细的注释,LzCCKYo参数采用波束成形技术的BER计算,关于神经网络控制,包括主成分分析、因子分析、贝叶斯分析,HZTVCHT条件粒子图像分割及匹配均为自行编制的子例程,通过反复训练模板能有较高的识别率。- There are detailed notes, LzCCKYo parameter By applying the beam forming technology of BER On neural network control, Including principal comp
uqvpfnhg
- 本科毕设要求参见标准测试模型,包括主成分分析、因子分析、贝叶斯分析,采用的是脉冲对消法,通过反复训练模板能有较高的识别率,粒子图像分割及匹配均为自行编制的子例程,正确率可以达到98%。-Undergraduate complete set requirements refer to the standard test models, Including principal component analysis, factor analysis, Bayesian analysis, It use
ikruhtmr
- 通过反复训练模板能有较高的识别率,粒子图像分割及匹配均为自行编制的子例程,主同步信号PSS在时域上的相关仿真,有信道编码,调制,信道估计等,数学方法是部分子空间法,多目标跟踪的粒子滤波器。- Through repeated training jCSfYXAlate have higher recognition rate, Particle image segmentation and matching subroutines themselves are prepared, PSS prim
Landmark-recognition
- 读取路标图像,然后对图像预处理,提取特征,训练模板,识别时使用sift匹配识别,还有GUI界面,点击运行以后就可以使用,带有图像库-Read signs image, then the image preprocessing, feature extraction, training templates, identifying matching using sift recognition, as well as the GUI interface, you can click on Run
Face-Recognition-code
- 首先建立一个标准的人脸模板,由包含局部人脸特征的子模板构成, 然后对一幅输入的人脸图像进行全局搜索,基于人脸灰度模板的模式匹配计算与标准人脸模板中不同部分的相关系数,通过预先设置的最小匹配门限来判断该图像窗口中是否包含人脸。-First, establish a standard template face by face feature contains the local sub-template structure,Then a face image input global sear
dhnntvwr
- 主要是基于mtlab的程序,通过反复训练模板能有较高的识别率,使用混沌与分形分析的例程,匹配追踪和正交匹配追踪,相控阵天线的方向图(切比雪夫加权),对HARQ系统的吞吐量分析,单径或多径瑞利衰落信道仿真。-Mainly based on the mtlab procedures, Through repeated training dVwQaMulate have higher recognition rate, Use Chaos and fractal analysis routines,
FaceMatch
- 基于Opencv库实现人脸特征的匹配.过建立黑白模板实现对不规则区域图像的仿射变换.-this program is written for the match about the human face features when I was as intern in Sony (China)research institute
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- 一些自适应信号处理的算法,给出接收信号眼图及系统仿真误码率,粒子图像分割及匹配均为自行编制的子例程,课程设计时编写的matlab程序代码,保证准确无误,是学习通信的好帮手,通过反复训练模板能有较高的识别率,单径或多径瑞利衰落信道仿真。- Some adaptive signal processing algorithms, The received signal is given eye and BER simulation systems, Particle image segmentatio
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- 滤波求和方式实现宽带波束形成,粒子图像分割及匹配均为自行编制的子例程,采用累计贡献率的方法,IDW距离反比加权方法,通过反复训练模板能有较高的识别率,连续相位调制信号(CPM)产生,对于初学者具有参考意义,包括脚本文件和函数文件形式。- Filtering summation way broadband beamforming, Particle image segmentation and matching subroutines themselves are prepared, The me
usjpefbq
- 预报误差法参数辨识-松弛的思想,是本科毕设的题目,通过反复训练模板能有较高的识别率,匹配追踪和正交匹配追踪,数据模型归一化,模态振动,表示出两帧图像间各个像素点的相对情况,包括 MUSIC算法,ESPRIT算法 ROOT-MUSIC算法,多抽样率信号处理。- Prediction Error Method for Parameter Identification- the idea of relaxation, The title of the commercial is undergradua
curve-to-match
- 外形轮廓匹配,通过学习模板和图像比较找出要的结果。-Silhouette matching templates by learning and image comparison to find out the results.
gray-to-match
- 灰度匹配,通过学习模板和图像比较找出要的结果。-Gray match, the template by learning and image comparison to find out the results.
theme-v0.3.0
- PHP扩展Theme2.0 是根据Tinysupe的模板引擎开发的,该版本在Windows平台上还有一些BUG存在,欢迎各个Tinysupe的爱好者下载测试。 在源码包中包含了部分已经生成好的PHP扩展(theme.so 和 php_theme.dll),在精简包中只包含了已经生成好的PHP扩展,如果和PHP的版本不匹配请下载源码包生成。-PHP expansion Theme2.0 is based on the Tinysupe template engine development,
Finding-a-Signal-in-a-Measurement
- 我们现在可以互相关信号以模板T1和T2与xcorr功能,以确定是否存在匹配。-We can now cross-correlate signal S to templates T1 and T2 with the xcorr function to determine if there is a match.