搜索资源列表
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
ImageFeatureExtractionAndMatchingAlgorithmAndItsIm
- 图像特征提取与匹配算法研究及其在印刷品图像检测中的应用-Image feature extraction and matching algorithm and its image in the print detection
3dpoint
- 在三维人脸建模中特征点的提取方法，文章中对该方法进行详尽的描绘，对做三维图像来说是很好的参考资料-Face in the three-dimensional modeling of the feature point extraction method, article, the method described in detail on the three-dimensional image is to do a very good reference
stabilization
- 介绍了数字图像稳像算法的整个流程,包括三部分:运动估计、运动决定和运动补偿。重点介绍了运动估计算法和运动补偿中的滤波算法 详细阐述了几种最基本的运动估计算法,其它的运动估计算法可以通过这些基本算法延伸发展得到 -The results show that the proposed method can pick up the image feature points effectively and make sure the precision and real time property.
Texture_Segmentation_Diffusion_Feature_Space
- 数字图像处理中的散度特征空间中的无监督的图像纹理分割-Digital image processing in the feature space of divergence Unsupervised texture segmentation of images
scalfeaturedescripionformatching
- 图像特征提取领域的一个小研究，可以提取其点特征，再进行特征描述和特征匹配。鲁棒性很强。-The field of image feature extraction, a small study of its points can be extracted features, further characterization and feature matching. Strong robustness.
Rapid_Object_Detection
- A very fast and robust object detection framework. A very simple set of Haar like box features A commensurating Image representation (that enables fast calculation of features, feature scaling and normalization) Efficient feature selectio
amfg07-demo-v1.tar
- This code implement method described in paper Enhanced Local Texture Feature Sets for Face Recognition under Difficult Lighting Conditions
Hproj
- 实现水槽沙波激光照片沙地波形提取功能。主要用到了水平投影的算法实现了对图像很好的处理。-To achieve laser tank sandwave Extraction feature photos sand wave. The main use of the horizontal projection of the algorithm achieved a very good handle on the image.
SIFT
- 两份SIFT的重要资料：Distinctive Image Features from Scale-Invariant Keypoints（by David G. Lowe）,SIFT特征匹配技术讲义(by 赵辉)-SIFT two important information: Distinctive Image Features from Scale-Invariant Keypoints (by David G. Lowe), SIFT feature matching technical
ImageProcessing
- 提供VC++图像处理，包括RGB转HSV，指纹识别，离散余弦转换，条码生成，手势识别，矩特征提取等-To provide VC++ image processing, including the RGB switch to HSV, fingerprint recognition, discrete cosine transform, barcode generation, gesture recognition, feature extraction, etc. Moment
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!
imagesearch
- 研究生毕业是编写的图像检索的程序，有相似度匹配，特征提取，检索运行效果好-Graduate school is to write the image retrieval process, there is similarity matching, feature extraction, retrieval operation good results
HarrisCorner
- 图像特征Harris Corner角点的提取 -Harris Corner corner image feature extraction
DetectionofTonguesCrackBasedonAdaptiveThreshold.ra
- 摘 要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不 适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并, 对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的 舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。-Tongue’ s crack is a very important part of herbal
cornerdetect
- 图像中的角点包含大量的信息，在计算机视觉中扮演重要角色，在许多应用中角点用作特征点，例如图像配准、运动目标跟踪等。鉴于此，学者们提出很多角点检测方法。例如Hans EMoravec在1977年提出的Movavec算法，Chris Harris和Mike Stephens于1988年提出的Harris算法，以及MirosavTrai．kovic和MarkHedley提出的Trajkovic算法等“卅。角点检测的另一个途径是计算轮廓的曲率函数，因为角点是曲率函数的最大值，因此很容易通过阈值的方法检测
Gabor_Filtering
- 采用matlab，实现了gabor滤波的核心功能-gabor filter is very famous and really useful for texture feature extraction and image retrivel. attached code is wrriten well using matlab. More detail can be referenced in the paper <texture features for browsing and ret
efinger.src
- 这是一个完整的指纹识别程序，它包括了直方图均衡，Gabor滤波图像增强，方向图过滤，纹理细化，特征提取及特征匹配。其中，特征匹配包含了3种匹配方法，另外还附有PPT，非常值得研究。-This is a complete fingerprint recognition program, which includes the histogram equalization, Gabor filter image enhancement, pattern filtering, texturing, th
pcasift
- 对虹膜识别的图像预处理各个步骤和虹膜图像特征提取 过程进行了研究，提出了一种虹膜定位算法-The image of the iris recognition iris image preprocessing steps and feature extraction process is studied, presents a iris location algorithm
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- 近年来，随着互联网的高速发展，网上的多媒体信息也急剧增加，这些多媒体信息以图像为主。如何从浩瀚的图像数据库中快速、准确地找出所需要的图像，己成为一个备受关注的研究课题。有效地组织、管理和检索大规模的图像数据成为迫切需要解决的问题。于是基于内容的图像检索(Content-Based Image Retrieval: CBIR)作为一个崭新的研究领域出现了。 本课题拟研究、分析彩色图像红、绿、蓝三基色直方图的生成、特征提取和相似度等问题，应用图像的颜色信息—三基色直方图对图像进行检索。针对基于颜