Description: 针对基于最小二乘法的ICP 曲面匹配算法难以处理待比较曲面的局部大变形问题, 提出一种改进算
法。即采用遗传算法确定曲面初始相对位置以保证匹配优化结果为全局最优值, 利用ICP 算法匹配结果构造
偏差阈值, 以此阈值过滤点群后再以最小二乘法进行匹配处理, 消除局部大变形影响, 获得合理的变换矩阵。以此变换矩阵变换初始点群再进行误差计算, 从而获得理想的匹配结果-Least square method based on the ICP surface matching algorithm to be relatively difficult to deal with the local surface deformation problem, an improved algorithm. Genetic algorithm that is used to determine the relative position of the initial surface in order to ensure optimization of the results of matching the global optimum value, the use of ICP algorithm to match the results of structural deviation threshold, this threshold point group and then filtered to match the least squares processing, the elimination of local large deformation effects of the transformation matrix to obtain reasonable. Transformation matrix to transform the initial point of the calculation error of another group in order to achieve an ideal match Platform: |
Size: 342016 |
Author:chenruibao |
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Description: otsu算法确定二值化阀值，最大类间方差是由日本学者大津(OTSU)于1979年提出的,是一种自适应的阈值确定的方法,又叫大津法,简称OTSU。
-In computer vision and image processing, Otsu s method is used to automatically perform histogram shape-based image thresholding,[1] or, the reduction of a graylevel image to a binary image. The algorithm assumes that the image to be thresholded contains two classes of pixels (e.g. foreground and background) then calculates the optimum threshold separating those two classes so that their combined spread (intra-class variance) is minimal.[2] The extension of the original method to multi-level thresholding is referred to as the Multi Otsu method[3]. Platform: |
Size: 1024 |
Author:白痴 |
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Description: linux下(fedora版本)的cadence中编译4位全加器的实现, 在不同的阈值电压调解下观察点路的总体power和速度,以及逻辑的正确性. 可能会用到NCSU的FREEPDF工具包-this is a package of three projects, low-vth, high-vth, and optimum architecture vth four bit full adder design. In the environment of Cadence and then simulated in Hspice and linked to VIVA at last we use the nanosim. Platform: |
Size: 4353024 |
Author:ququmo |
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Description: 用最速下降法求最优化解
输入：f为函数名 grad为梯度函数
x0为解的初值 TolX,TolFun分别为变量和函数的误差阈值
dist0为初始步长 MaxIter为最大迭代次数
输出: xo为取最小值的点 fo为最小的函数值
f0 = f(x(0- Steepest Descent Method with Optimum Solution input: f as a function name grad is gradient function x0 for the solution of the initial TolX, TolFun variables and functions were error threshold dist0 as the initial step MaxIter maximum Diego passage number Output: xo to take the minimum point of fo is the smallest function value f0 = f (x (0)) Platform: |
Size: 1024 |
Author:华 |
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Description: In Analog systems, the chief objective is the fidelity of reproduction of waveforms, hence, the suitable performance criterion is the output signal to noise ratio. The choice of this criterion stems from the fact that the signal to noise is related to ability of the listener to interpret a message. Matched filter is the optimum linear filter that maximizes the output signal to noise ratio. The Matched filter is optimum in the sense that it maximizes the signal amplitude to rms noise ratio at the decision-making instant. Although it is reasonable to assume that maximization of this signal to noise ratio will minimize the detection error probability, we have not proved that threshold detection is the optimum method from the detection error point of view. It will be shown that when the channel noise is white Gaussian, the matched filter receiver is indeed the optimum receiver that minimizes the detection error probability.- In Analog systems, the chief objective is the fidelity of reproduction of waveforms, hence, the suitable performance criterion is the output signal to noise ratio. The choice of this criterion stems from the fact that the signal to noise is related to ability of the listener to interpret a message. Matched filter is the optimum linear filter that maximizes the output signal to noise ratio. The Matched filter is optimum in the sense that it maximizes the signal amplitude to rms noise ratio at the decision-making instant. Although it is reasonable to assume that maximization of this signal to noise ratio will minimize the detection error probability, we have not proved that threshold detection is the optimum method from the detection error point of view. It will be shown that when the channel noise is white Gaussian, the matched filter receiver is indeed the optimum receiver that minimizes the detection error probability. Platform: |
Size: 2206720 |
Author:nani |
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Description: 针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷
入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。
该方法考虑了图像中像素点灰度 邻域灰度均值对作为阈值对图像进行分割 利用混沌运
动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜
索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索
时间, 提高了收敛率。-Calculation of its large capacity and particle swarm algorithm is easy to fall to strike the best threshold for the two-dimensional entropy image segmentation method
Into the local optimum and slower, the proposed two-dimensional entropy image segmentation method based on chaotic particle swarm optimization algorithm.
The method takes into account the image pixel the gray neighborhood average gray value as a threshold for image segmentation chaotic transport
Dynamic randomness, ergodicity and initial value sensitivity of chaotic particle swarm optimization algorithm with the threshold method in two-dimensional space for the global search
On request. Experimental results show that the entropy method of image segmentation method based on chaotic particle swarm optimization algorithm for threshold optimization to reduce the search
Time and improve the convergence rate. Platform: |
Size: 1820672 |
Author:张泰然 |
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Description: 清空环境变量
网络结构建立
遗传算法参数初始化
迭代求解最佳初始阀值和权值
遗传算法结果分析
把最优初始阀值权值赋予网络预测
BP网络训练
BP网络预测
清空环境变量-Empty the environment variable
Established network structure
Genetic algorithm parameter initialization
Iterative Solution optimum initial thresholds and weights
Analysis of Genetic Algorithms
The optimal initial threshold value is assigned to the right network prediction
BP network training
BP network prediction
Empty the environment variable Platform: |
Size: 2048 |
Author:jacy |
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Description: 学习使用OpenCV，对输入的一段彩色视频，用OpenCV实现以下功能或要求:
1. 对输入视频的每一帧图像都用同一个阈值进行二值化；
2.在每帧二值化图像上叠加上含自己学号与姓名等信息的版权字幕；
3. 在处理的过程中，实时显示每帧图片处理之后的效果；
4.将所有这些二值化图像按视频原来顺序合成输出一个视频文件，按原输入视频播放速度的两倍合成；
5. 做成如下的命令行格式，xxx.exe 输入视频文件名 二值化阈值 输出视频文件名（例如 MyBiVideo.exe input.avi 50 output.avi ）
这里的二值化有两种选择，可以手动收入阈值，也可以直接用OTSU算法的较优阈值直接二值化。-Learn to use OpenCV, for some color video input, with the OpenCV following functions or requirements:
1. Each frame of the input video images are binarized using the same threshold value
2. superposed on the binarized image of each frame containing the copyright on the number and the name of their own learning subtitles other information
3. During processing, real-time display after processing each frame
4. All of these binarized image by synthesizing the video output of a video sequence of the original document, the original input composite video playback speed twice
5. made the following command line format, xxx.exe input video file name binary threshold value of the output video file name (eg MyBiVideo.exe input.avi 50 output.avi)
Here there are two binary choice, you can manually income thresholds, you can directly use the optimum direct binarization threshold through OTSU algorithm. Platform: |
Size: 5449728 |
Author:chenyingshu |
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Description: 利用最大熵法求取最优阈值来对目标图像进行分割，程序体现了最优阈值的迭代求法。-To obtain the optimal threshold segmentation of the target image using the maximum entropy method, the program of optimum threshold method. Platform: |
Size: 1024 |
Author: |
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Description: Image segmentation by region growing method is
robust fast and very easy to implemented, but it suffers from:
the threshold problem, initialization, and sensitivity to noise.
Genetic algorithms are particular methods for optimizing
functions they have a great ability to find the global
optimum of a problem. In this paper, we used genetic
algorithms to get over the threshold problem. We have
proposed a segmentation method based on region growing
and genetic algorithms.-Image segmentation by region growing method is
robust fast and very easy to implemented, but it suffers from:
the threshold problem, initialization, and sensitivity to noise.
Genetic algorithms are particular methods for optimizing
functions they have a great ability to find the global
optimum of a problem. In this paper, we used genetic
algorithms to get over the threshold problem. We have
proposed a segmentation method based on region growing
and genetic algorithms. Platform: |
Size: 210944 |
Author:Merin Iliparambil |
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Description: 为了提高小波分析方法在混沌去噪中的自适应能力，对不同尺度下的小波信号设定调节因子，根据混沌序列
关联维的大小确定最优阈值。为了提高寻优效率，采用遗传算法全局自适应搜索最优阈值。利用该方法对Lorenz混沌时
间序列进行了去噪分析，结果表明所提方法是非常有效的。-For the purpose of improving adaptive performance of chaotic signals de-noising with wavelet transform，a
floating parameter is set to regulate the threshold of wavelet signal on different scales according to the correlation dimension
of chaotic time series．The genetic algorithm is helpful tO obtain global optimum thresholds and tO reduce much time wasted
by the adaptive searching computation．De-noising for Chaotic time series generated by Lorenz system is simulated to corn—
pare with other methods，and the results showed that the proposed method iS effective Platform: |
Size: 288768 |
Author:张洋 |
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Description: 该实例程序通过改进灰度直方图双峰法，实现了迭代求全局最佳阈值，对于前背景灰度范围差异明显的图像有良好的分割效果。(By improving the gray histogram Shuangfeng method, the example program achieves the global optimum threshold by iteration, and has good segmentation effect for the images with obvious differences in the gray range of the previous background.) Platform: |
Size: 168960 |
Author:阿迪斯阿斯蒂芬
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Search - optimum threshold