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[Special Effects] circlefitting DL : 1: 最小二乘法拟合圆vc实现，最小二乘法(least squares analysis)是一种数学优化技术，它通过最小化误差的平方和找到一组数据的最佳函数匹配。最小二乘法是用最简的方法求得一些绝对不可知的真值，而令误差平方之和为最小。-least squares fitting round vc realized, least-squares method (least squares analysis) is a mathematical optimization techniques, It error by minimizing the square and a group of data to find the best matching function. Least-squares method is the most simple method to derive absolutely true value unknown, and so the sum of squared errors to the minimum.
Date : 2008-10-13 Size : 183kb User : 林楚
[Special Effects] circlefitting DL : 0: 最小二乘法拟合圆vc实现，最小二乘法(least squares analysis)是一种数学优化技术，它通过最小化误差的平方和找到一组数据的最佳函数匹配。最小二乘法是用最简的方法求得一些绝对不可知的真值，而令误差平方之和为最小。-least squares fitting round vc realized, least-squares method (least squares analysis) is a mathematical optimization techniques, It error by minimizing the square and a group of data to find the best matching function. Least-squares method is the most simple method to derive absolutely true value unknown, and so the sum of squared errors to the minimum.
Date : 2025-12-29 Size : 183kb User : 林楚
[Special Effects] iseTools.tar DL : 0: matlab视频编码压缩工具源代码，具体内容不详-matlab video coding compression tools source code, the specific content of an unknown
Date : 2025-12-29 Size : 8.29mb User : leo
[Special Effects] chengxu DL : 0: 基于仿射变换来解算摄影测量构像方程的未知参数-Based on the affine transformation to calculate Photogrammetry conformation of the unknown parameters of equation
Date : 2025-12-29 Size : 346kb User : cyrser
[Special Effects] icpCpp DL : 0: ICP是用来匹配两组未知点，可以用于图像处理等方面，速度快，但需要选择好初始参数-ICP is used to match two sets of unknown points can be used in areas such as image processing speed, but need to select a good initial parameters
Date : 2025-12-29 Size : 20kb User : aa
[Special Effects] chirplet_analasis DL : 0: 一种自适应chirplet分解的快速算法针对信号自适应chirplet分解未知参数多、实现起来比较困难的特点，文献[1]提出了一种新的chirplet分解快速算法。该算法利用计算信号的二次相位函数，得到其能量分布集中于信号的调频率曲线上的结论，此时通过谱峰检测可同时获得chirplet调频率、时间中心和幅度的估计；然后通过解线性调频技术获得其初始频率和宽度的估计，仿真结果验证了本文算法的有效性。 -Chirplet an adaptive decomposition algorithm for rapid adaptive signal decomposition Chirplet many unknown parameters, is more difficult to achieve the characteristics of the literature [1] proposed a new fast algorithm Chirplet decomposition. The algorithm calculating the signal function of the second phase, its energy distribution to be concentrated in the signal modulation frequency curve on the conclusions, this time through the spectral peak detection can be obtained simultaneously Chirplet tune the frequency, timing and magnitude of the estimated center then through the solution line technology of FM frequency and the width of the initial estimates, the simulation results verify the effectiveness of the algorithm.
Date : 2025-12-29 Size : 79kb User : nanzhewan
[Special Effects] test2 DL : 0: 运动方向未知的运动模糊图像盲复原，包括移动像素和角度 -Movement direction of the motion-blurred images unknown blind rehabilitation, including moving pixels and angle
Date : 2025-12-29 Size : 1kb User : Echo
[Special Effects] Hough DL : 0: 利用Hough变换实现半径未知的圆形物体的检测-Use Hough transform to achieve a circular radius of an unknown object detection
Date : 2025-12-29 Size : 12kb User : Beata
[Special Effects] circle-detection DL : 0: 采用hough变换对半径未知的圆进行检测-Using hough transform to detect the circle radius of the unknown
Date : 2025-12-29 Size : 2kb User : sss
[Special Effects] gspm DL : 0: 自己本机测试最快时60帧/秒,局域网传输只测试一次,结果很让我失望,原因不明~~~~ 说下我的思路过程(我认为过程很重要!) 分块比较+压缩传输与以前那个内存流比较的优缺点: 内存流比较能找到最精确的找到图片差异,但每次都要压缩相同大小的数据,大家可以测试下,那个算法传输瓶颈是压缩算法,最费时间和CPU 分块比较+压缩传输能有效的减少压缩数据量,但缺点也很明显,比较图片的效率肯定没内存流比较高,要加快传输只能找到更好的算法我选择的是后者,开始的时候是直接把截下来的图片分成n块,然后逐块和上一个图片比较,不同就放到流中压缩传送,不过写完测试时很是郁闷,Cpu占用不说,在自己电脑上根本就突破不了16帧,当时就苦想能节约时间的方法(当时做梦都在想^.^),终于在一次被吵醒后来了灵感,每次都要把图片分成n块,这也很占时间啊,有没有更好的办法呢?觉也睡不着了... 具体实现就看代码吧^_^-Their own tests of this machine, when the fastest 60 frames/sec, LAN transmission test only once, the result will let me down, for reasons unknown ~ ~ ~ ~ wrote down my thought process (I think the process is very important!) Compared+ block compression and transmission compared with the previous flow advantages and disadvantages of that memory: Memory stream more able to find the most accurate picture to find differences, but the same size every time compressed data, we can test, that algorithm is a compression algorithm transmission bottlenecks, the most time-consuming and Comparison of CPU Block+ compression and transmission can effectively reduce the amount of data compression, but the disadvantage is also apparent, comparing the efficiency of the picture, certainly not the memory stream is relatively high, to speed up the transfer can only find a better algorithm
Date : 2025-12-29 Size : 577kb User : 高速屏幕传输演示代码
[Special Effects] selfadaptingbackgroundrestoration DL : 0: 提出了基于自适应背景恢复的差减算法。该算法可在背景未知的情况下，对任意运动目标都能实时、有效地进行自动分割-Proposed restoration based on adaptive background subtraction algorithm. The algorithm can be in the background unknown circumstances, for any moving object can be real-time, effectively automatic segmentation
Date : 2025-12-29 Size : 130kb User : 曹妍妍
[Special Effects] rice_detection DL : 0: 利用机器视觉系统代替人眼获取各项大米参数,再参照国标对其进行等级划分。在此基础上, 利用MATLAB软件的神经网络工具箱在数理统计基础上完成检测模型的构建,从而实现对未知大米外特性的评判,并为检测大米综合品质奠定了基础。-rice detection.At p resent, the evaluation method of the rice quality in China is still at the level of naked eye observation. How to classify different varieties of rice through the quality parameters based on the adop ted evaluation criteria becomes a new research top ic. In this paper, the machine vision- based method is used in studying the rice quality. On the basis of the evaluation criteria, different kinds of rice are classified. And according to the usage of neural network, the detec2 tion model is established, so it can lay the foundation for the p rediction of the unknown kinds of rice in the future.
Date : 2025-12-29 Size : 8kb User : wangjianshe
[Special Effects] ZuiXiaoErCheng DL : 0: 利用目标以前的坐标点完成目标未来未知位置的预测，分别利用一个到五个点来进行预测-Using the coordinates of points before the completion of target objectives of the forecast future unknown location, respectively, using 1-5 point forecast
Date : 2025-12-29 Size : 1kb User : yanzongqun
[Special Effects] shibie DL : 0: 基于奇异值分解的人脸识别方法梁毅雄龚卫国潘英俊李伟红刘嘉敏张红梅提出了一种将傅里叶变换和奇异值分解相结合的人脸自动识别方法.首先对人脸图像进行傅里叶变换,得到其具有位移不变特性的振幅谱表征.其次,从所有训练图像样本的振幅谱表征中给定标准脸并对其进行奇异值分解,求出标准特征矩阵,再将人脸的振幅谱表征投影到标准特征矩阵后得到的投影系数作为该人脸的模式特征.然后,对经典的最近邻分类器算法进行了改进,并采用模式特征之间的欧式距离作为相似性度量,从而完成对未知人脸的识别.采用ORL (Olivetti Research Laboratory)人脸库对本文提出的人脸识别方法进行验证,获得了100.00 的识别率.实验结果表明,本方法优于现有的基于奇异值分解的人脸识别方法,且对表情、姿态变换等具有一定的鲁棒性. -Face recognition based on singular value decomposition method Deliberate simultaneously Gong Weiguo Li Wei Hung Stephen Lau, Hong-Mei Zhang Ying-Jun Pan Paper, a Fourier transform and singular value decomposition of the combination of automatic face recognition. First of all, the face image by Fourier transformation, it has the same characteristics of the displacement amplitude spectra. Secondly, all training The amplitude spectrum of the sample images given in standard face representation and its singular value decomposition, find the standard characteristic matrix, then the amplitude of spectral characterization of human faces projected onto the standard characteristic matrix of projection coefficients obtained as the face of the model features . Then, the classical nearest neighbor classifier is improved, and the use of Euclidean distance between pattern features as the similarity measure, thus completing the identification of unknown human faces. using ORL (Olivetti Research La
Date : 2025-12-29 Size : 57kb User : houhj
[Special Effects] Bayes-Iris DL : 0: 根据贝叶斯原理设计的一个简单的分类器，利用已知样本数据训练后，分类器就可以对未知样本进行分类。（实验时采用的是Iris数据集。）-According to the design of a simple Bayesian classifier, using the known training sample data, the classifier can classify the unknown samples. (Experiments using the Iris data set.)
Date : 2025-12-29 Size : 9kb User : lhb
[Special Effects] scrambling DL : 0: 经过置乱变换的水印再用混沌技术进行加密,在密钥未知的前提下,非授权者无法获取嵌入的数字水印,从而提高了水印系统的安全性-After scrambling transformation chaotic watermarking technology and then encrypted in the key premise of the unknown, unauthorized persons can not obtain the embedded watermark, so as to enhance the security of the watermarking system
Date : 2025-12-29 Size : 5kb User : 朱晓峰
[Special Effects] 2010ICIP-Multiple-object-track DL : 0: 2010ICIP会议的最新文章，结合时空信息实现对目标的跟踪。-This paper presents a data-oriented tracking framework which aims to recover the spatio-temporal trajectories for an unknown number of interacting objects appearing and disappearing at arbitrary times.
Date : 2025-12-29 Size : 866kb User : kongsuhong
[Special Effects] SubPx DL : 0: 图像处理中常遇到“亚像素”这个词。亚像素实际上不存在，但是在想象中存在。于是用数学的方法计算出它的值。示例中将一幅图的高和宽都扩大到5倍，造成原来相邻两像素不相邻了，中间间隔了好几个像素单位，这些像素怎样定义它们，简单的，数学上用双线性插值的方法求出未知的像素。本程序提供一个代码示例，供参考，希望对您有帮助。-Frequently encountered in image processing "sub-pixel" is the word. Sub-pixel does not actually exist, but exist in the imagination. So using mathematical methods to calculate its value. Sample will be a picture height and width are expanded to five times, resulting in two adjacent original pixels are not adjacent, and an interval of several pixels, the pixels how to define them, a simple, mathematically using bilinear interpolation method to calculate the unknown pixels. This program provides a code sample, for reference, hope you have help.
Date : 2025-12-29 Size : 387kb User : xuxiangxing
[Special Effects] KL DL : 0: 基于KL变换的特征提取的方法。选取数据库中的部分样本（每个人的前5张图片）作为训练样本，其余作为未知的测试样本。从训练样本中得到KL变换矩阵，然后对训练样本和测试样本都进行变换，用变换后的数据作最近邻识别，距离可以为对应灰度值之差的平方和，统计识别率。-KL transform based feature extraction method. Select the database part of the sample (each person' s top 5 pictures) as the training samples, the rest as unknown test samples. Training samples obtained from KL transform matrix, then the training samples and test samples for transformation, with the transformed data for the nearest neighbor recognition from the corresponding gray value for the difference of squares, statistical recognition rate.
Date : 2025-12-29 Size : 3kb User : 刘峰
[Special Effects] 03 DL : 0: 类的目的就是根据现有的图像特征建立一个分类器，能够对未知的图像类型进行预测。在现有众多分类算法中，贝叶斯分类器由于其坚实的数学理论基础并能综合先验信息和数据样本信息，成为"-3前机器学习和数据挖掘的研究热点之一。本文论述了内容图像检索中基于贝叶斯分类器的图像分类技术。介绍了贝叶斯分类器，叙述了利用贝叶斯分类器进行图像分类的方法，以及图像特征的分布假定。最后通过对分类器的探讨，总结了贝叶斯估计分类的不足。-The purpose of class is based on an existing image features to create a classifier able to predict the unknown image type. Many of the existing classification algorithm, the Bayesian classifier because of its solid mathematical theory-based and comprehensive information prior information and data samples, a " -3 before the machine learning and data mining research focus of this paper discusses the Content-based Image Retrieval Bayesian classifier image classification techniques. introduced Bayesian classifier, described the use of Bayesian classifier for image classification methods, and the distribution of image features is assumed finally by classifier discussion summarizes the classification of the lack of Bayesian estimation.
Date : 2025-12-29 Size : 254kb User : 刘东

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