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K_Means_image_compression
- K means algorithm is performed with different initial centroids in order to get the best clustering.
- The total cost is calculated by summing the distance of each point to its cluster centre and then summing over all the clusters.Based on the minimum overall cost achieved during each iteration of iterKMeans the pixel assignment to their respective clusters are made and final compressed image is obtained. This algorithm will run slower as the number of clusters , size of the image and number of iterations increase.
- 2013-07-26 15:49:00下载
- 积分：1
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level_fuzzy
liquid level control using fuzzy logic controller
- 2014-09-07 06:17:04下载
- 积分：1
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chongdiefenkuai
自己编的图像重叠分块再重新合成的程序。使用matlab。(Re-synthesis process images overlap own the block. Use matlab.)
- 2014-03-03 11:23:46下载
- 积分：1
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mterm
用matlab2007实现的一个term客户端，可以用于上BBS(Matlab2007 achieved using a term client, can be used on the BBS)
- 2008-06-11 10:09:23下载
- 积分：1
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objectDetect
detect object in simple and uniform background.
- 2015-02-19 18:21:01下载
- 积分：1
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chap3_10_DMRAS_ordn
说明： 这是关于自适应的一个m文件，希望对大家有用(This is an m on the adaptive document, we hope to be useful)
- 2011-03-21 14:17:59下载
- 积分：1
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Matlab-parallel-and-distributed
有关matlab并行以及分布式运算的书籍，适合初学者使用。(About matlab parallel and distributed computing books for beginners to use.)
- 2013-12-28 17:37:56下载
- 积分：1
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mleach2222
leach protocol for wsn
- 2012-04-15 03:09:31下载
- 积分：1
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sift
1 SIFT 发展历程
SIFT算法由D.G.Lowe 1999年提出，2004年完善总结。后来Y.Ke将其描述子部分用PCA代替直方图的方式，对其进行改进。
2 SIFT 主要思想
SIFT算法是一种提取局部特征的算法，在尺度空间寻找极值点，提取位置，尺度，旋转不变量。
3 SIFT算法的主要特点：
a) SIFT特征是图像的局部特征，其对旋转、尺度缩放、亮度变化保持不变性，对视角变化、仿射变换、噪声也保持一定程度的稳定性。
b) 独特性(Distinctiveness)好，信息量丰富，适用于在海量特征数据库中进行快速、准确的匹配[23]。
c) 多量性，即使少数的几个物体也可以产生大量SIFT特征向量。
d) 高速性，经优化的SIFT匹配算法甚至可以达到实时的要求。
e) 可扩展性，可以很方便的与其他形式的特征向量进行联合。
4 SIFT算法步骤：
1） 检测尺度空间极值点
2） 精确定位极值点
3） 为每个关键点指定方向参数
4） 关键点描述子的生成
本包内容为sift算法matlab源码(1 SIFT course of development
SIFT algorithm by DGLowe in 1999, the perfect summary of 2004. Later Y.Ke its description of the sub-part of the histogram with PCA instead of its improvement.
2 the SIFT main idea
The SIFT algorithm is an algorithm to extract local features in scale space to find the extreme point of the extraction location, scale, rotation invariant.
3 the main features of the SIFT algorithm:
a) SIFT feature is the local characteristics of the image, zoom, rotate, scale, brightness change to maintain invariance, the perspective changes, affine transformation, the noise also maintain a certain degree of stability.
b) unique (Distinctiveness), informative, and mass characteristics database for fast, accurate matching [23].
c) large amounts, even if a handful of objects can also produce a large number of SIFT feature vectors.
d) high-speed and optimized SIFT matching algorithm can even achieve real-time requirements.
e) The scalability can be very convenient fe)
- 2012-05-25 15:31:16下载
- 积分：1
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Romberg
通过输入区间端点a和b以及精度，初始等分数和最大外推层数来近似f(x)在a到b上的积分！(By entering a and b as well as the interval endpoint accuracy, the initial fraction and the like to approximate the maximum number of layers extrapolation f (x) at the points a to the b!)
- 2014-11-29 20:15:20下载
- 积分：1
