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fayeboy1984
- 此设计要求能够实现将医学图像进行识别的过程,包括了图像预处理、图像特征提取及分类判决三大模块。在预处理这一步中主要实现的是将彩色图像转换为灰度图像,灰度图像的二值化,直方图修正,去除干扰、噪声以及差异,边缘增强等;第二模块是图像的特征提取。由于对象的物理与几何特性差异,在影像中表现为局部区域的灰度产生明显变化,形成影像特征,而图像特征提取就是对其进行加工、整理、分析、归纳以便提取构成目标影像的特征,得到能反映图像内容区别于其他事物的本质特征;分类判决作为第三模块,则是要在第二步的基础上采用某种分
1
- 一种图像检索中纹理特征提取的方法。本文介绍了基于Gabor 滤波器和Gabor 小波变换提取纹理特征的分析方法, 以及对Gabor 小波进行了高斯归一化以提高对图像检索的速度和准确度。-An image retrieval texture feature extraction methods. This article based on Gabor filters and Gabor wavelet transform to extract texture feature analysis me
imagemosic
- 针对基于图像特征点的配准方法中对应特征对难以准确提取的问题,提出一种基于兴趣 点匹配的图像自动拼接方法。该方法首先利用Harris角检测器提取两幅图像中的兴趣点,并在此基 础上采用比较最大值法提取出对应兴趣点特征对,最后利用这些匹配特征对来实现图像的拼接。实 验结果表明,这种方法能有效地去除伪匹配特征对的干扰,同时降低了误匹配的概率-Feature points for image-based registration method of the corresponding char
neuralandwavelet
- 对采集到的电压信号进行小波包分解提取特征向量,再进行BP神经网络训练-On the acquisition of the voltage signal to the wavelet packet decomposition to extract feature vector and then BP neural network training
DatamininginChinesemedicalrecords
- 本研究中,我们研究了一种新的基于短语的特征提取算法。并把这种算法应用到中文真实病历的分类中,取得了较好的分类效果。-In this study,we employed a novel feature extract method--the phrase based feature extracting method.
SNN4ImageFeaturIPCAT2007
- Based on the information processing functionalities of spiking neurons, a spiking neural network model is proposed to extract features from a visual image. The network is constructed with a conductance-based integrate-and-fire neuron model and a set
tracking
- This paper proposes a new method of extracting and tracking a nonrigid object moving while allowing camera movement. For object extraction we first detect an object using watershed segmentation technique and then extract its contour points by a
mmsp08
- Feature extraction is a key issue in contentbased image retrieval (CBIR). In the past, a number of texture features have been proposed in literature, including statistic methods and spectral methods. However, most of them are not able to accu
imagefeatureextract
- 图像特征提取课件,很值得一看,讲解的比较好-image feature extract PPT very good!
sift5
- :研究了一种多目标识别算法,该算法用SUSAN角点形成SIFT特征点,采用阶梯图像金字塔结构实现尺度不变,为所有匹配点建立统一的超定线性方程组并对该方程组系数矩阵进行简 化使其维数降低一半,得到增广矩阵.对增广矩阵进行列变换,依据坐标转换的特性可从中提取多目标的稳定正常点,实现了快速分离多目标的匹配点. -: Study of a multi-target recognition algorithm using SUSAN corner formed SIFT feature point
work
- this file help to extract feature and then apply vector quantization to minimize the data
mypaper4
- To fully utilize the character of the bioradar echo signal, autocorrelation analysis, spectral estimation methods and time-frequency analysis are presented in this paper. These methods are employed to deal with no one, single people and multi-people
201204_SYJTTESWD
- 高精度的石英晶体测温: 通常,我们都在使用如热电偶,热电阻,热敏电阻,半导体或集成电路传感器....来测量温度,实际上,如果利用晶体来做温度传感器,其精度就会大幅度提高! 石英晶体的振荡频率会随温度的变化而发生微小的变化,利用这一特性,通过测量石英晶体振荡器的频率,就可司接测得相应的温度值,所以石英晶体谐振器还可用来进行温度的测量。测温石英晶体谐振器就属于这一类产品,它采用玻璃外壳封装软弓线电极,分辨率可达0.01℃-0·0001℃,适合作测温敏感元件。 这里
master_thesis
- 音乐领域中文实体关系抽取研究 实体关系抽取的任务是从文本中抽取出两个或者多个实体之间预先定义 好的语义关系。本文将实体关系抽取定义为一个分类问题,主要研究内容是 中文音乐领域的实体关系抽取。针对这一问题,本文首先构建了中文音乐实 体关系语料库,然后分别采用了基于序列模式挖掘的无指导的方法和基于特 征提取的有指导的方法来解决这一问题。 -Dissertation for the Master Degree in Engineering urgently needed to de
GPS-and-Linux-design
- 介绍了一种基于嵌入式Linux系统和ARM9处理器的手持式GPS数据采集、处理、显示接收机的设计过程。采用ARM-Linux和ARM9处理器的系统作为开发平台,控制OEM板接收导航信息,并给出了GPS数据采集系统详细的软件设计方案,给出了提取GPS特征数据的算法。这些对研完嵌入式系统应用、GPS定位及其在组合导航中的应用以及对OEM板的二次开发等都具有实用价值。 -An embedded Linux operating system and ARM9 processor-based hand
Active-contour-3-d-image
- 对具高噪声和低对比度三维图像的识别和分割算法进行了研究。基于活动轮廓模型,用Gabor变换提取图像的纹理特征,根据统计学信息假设,通过偏微分方程水平集和窄带方法求解,获得较基本活动轮廓的算法分割更光滑精确的物体轮廓-To a high noise and low contrast 3 d image recognition and segmentation algorithm was studied. Based on the active contour model, with Gabor t
Based-onSVM-target-tracking
- 计算Haar小波特征,用AdBaoost提取部分有代表性的特征共三种特征选择方法与SVM相结合进行目标跟踪的算法。 -The calculated Haar wavelet features to extract some of the typical characteristics of three feature selection method combined with SVM algorithm for target tracking AdBaoost.
MFCC-feature
- 通过matlab实现语音信号提取MFCC特征-To extract MFCC characteristics matlab voice signal
matlab-feature-extraction
- 提取灰度共生矩阵的分类作用,有利于后续的人工神经网络的进行-To extract the classification of the gray level co-occurrence matrix, is advantageous to the subsequent artificial neural network
New-folder
- for eeg signal feature extract