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adaptive_framing
- Use your own images to make picture frames The program adpframe.m makes picture frames and then frames an image using that frame. Some patterns are provided in the zipped file, which can be used to make frames and then frame images. Special Fe
imageprocessing
- 本人硕士阶段图像处理的课程报告，包括平滑，增强，恢复等程序，适合初学者使用-Master stage image processing programs, including smoothing, enhance and restore procedures for beginners
fun_pcnn
- 基于PCNN的特征提取,PCNN用于特征提取时，具体平移、旋转、尺度、扭曲等不变性，这正是许多年来基于内容的图像检索系统追求的目标，同时PCNN用于特征提取时，有很好的抗噪性。而且PCNN直接来自于哺乳动物视觉皮层神经的研究，具有提取图像形状，纹理，边缘的属性。用PCNN能很好地对图像进行签名，将二维的图像的特征提取成一维矢量签名。-Feature extraction of specified object is an important preprocessing stage in ma
resampling
- 粒子滤波改进的重采样程序，Performs the resampling stage of the SIR -Improved particle filter resampling procedure, Performs the resampling stage of the SIR
tuxiangpipei
- 三篇介绍图像匹配的学术论文，属于图像的预处理阶段的研究-3 Image Matching introduction of academic papers, images belong to the pre-processing stage of the study
BasedonprincipalcomponentanalysisoftheFaceRecognit
- 在特征提取阶段，研究了PCA, 2DPCA, (2D) 2PCA, DiagPCA, DiagPCA-F-2DPCA等多 种方法。不同于基于图象向量的PCA特征提取，由于2DPCA, (2D) ZPCA, DiagPCA和 DiagPCA-I-2DPCA的特征提取都直接基于图象矩阵，计算量小，所以特征的提取速度明 显高于PCA方法。-In the feature extraction stage, the study of the PCA, 2DPCA, (2D) 2PCA,
paper
- 高性能多阶有源带通滤波器设计,大家可以作为参考-Multi-stage high-performance active bandpass filter design, we can serve as a reference
demo
- opencv 图像处理范例程序，对于图像的处理阶段进行，给出效果图，初学者使用-opencv image-processing example of the procedure for image processing stage, given the effect of map, for beginners to use
machinevision
- 国内机器视觉、图像处理行业分析，对研究生阶段学习这个行业的要求，希望这个方向的研究生-Domestic machine vision, image processing, industry analysis, stage of post-graduate study and the requirements of the industry, I hope in this direction a good look at the post-graduate
Thin_proncesing
- 对输入的图像进行细化，输出细化后的图像 用于神经网络识别字符的前期操作-Refinement of the input image, the output image after thinning for the neural network to recognize characters in the early stage of operation of
256colorImageConvertGrayImage
- 256色图与灰度图之间的转换，可用作图像或视频操作的预处理阶段，VC平台。-256-color map and the grayscale conversion between the operation can be used as image or video pre-processing stage, VC platform.
Tiff
- tiff格式详细分析级VC++基本处理介绍，学习使用-tiff format, detailed analysis of the basic processing stage VC++ introduction and learning to use
siftDemoV4
- 非常有名的SIFT变换程序，实现了多级变换检测！-A very well-known SIFT conversion process to achieve a multi-stage transformation test!
zifushibeiyufenge
- 复杂背景下车牌定位与字符分割算法研究 本文在简要介绍国内外车牌识别技术研究现状的基础上，对车牌定位算法及字符分 割算法进行了深入的研究，主要完成以下工作： 车牌的定位算法设计阶段，本文提出了一种综合利用车牌多重特征的定位算法。该 算法充分利用了车牌的纹理，色彩及车牌长宽比等特征。经过水平梯度化，二值化，滤 波，区域连通、连通域标记筛选，色彩匹配等几个步骤，最终达到了复杂背景下汽车牌 照的定位。-Complex background license plate loc
zsttlb
- 毕业设计：指数同台滤波程序与巴特沃斯。高斯滤波器相比较！-Graduation: Index on the same stage filtering process and Butterworth. Gaussian filter comparison!
canny
- Canny 算子 是一个具有滤波、增强和检测的多阶段的优化算子。在进行处理前，Canny 算子先利用高斯平滑滤波器来平滑图像以除去噪声( 即用高斯平滑滤波器与图像作卷积) 。-Canny operator is a filtering, enhancement and optimization of multi-stage detection operator. Before treatment, Canny operator first use Gaussian smoothing fi
exa2.8
- 本程序是上一个例子2.7的简化。每个独立阶段释放内存简化图像处理流程。-This program is 2.7 on a simplified example. Simplify each individual stage of free memory, image processing process.
canny_color
- The Canny edge detection operator was developed by John F. Canny in 1986 and uses a multi-stage algorithm to detect a wide range of edges in images. Most importantly, Canny also produced a computational theory of edge detection explaining why the tec
A-real-world-system-for-human-motion-detection-an
- In this thesis we present an operational computer vision system for real-time detection and tracking of human motion. The system captures monocular video of a scene and identifies those moving objects which are characteristically human. This serves a
multicontourlet-project-phase-1
- MCT is composed of two-stage filter banks similar to that of the contourlet transform (CT) [8]. The first stage filter banks implement multiwavelet decomposition, which capture the point singularity effectively, in contrast to the Laplacian p