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- 二值化、腐蚀和膨胀、填充、边缘提取运算matlab中用法举例-Example of erosion and dilation operator usage
bwperim
- 实现提取2值图象的边缘,根据MATLAB中的bwperim函数改编的C函数.-2 the value of the realization of extracting the edge image, in accordance with MATLAB in the adaptation of bwperim function C function.
work
- 在DCT域进行图像检索，分别采取了对DCT块的边缘类型提取以及纹理特征提取两个方法-Image Retrieval in DCT domain, DCT blocks were taken on the edge of the type and texture feature extraction method of extracting the two
edgedetec
- 用matlab实现边缘提取，应用于医学图像效果不错，抑制噪声很好-Edge detection using matlab implementation, good results for medical images, good noise suppression
MedicalImageSegmentation
- 医学图像分割的实验报告(包含源程序)，主要内容包括：不同算子（Sobel、Prewitt、Roberts、Laplacian）的边缘提取效果分析；阈值分割；以及watershed方法的分割讨论。-The implementation and discussion for fundamental medical image segmentation algorithms, including edge extracting algorithm, thresholding methods and w
CannyEdgeDetection
- Canny边缘检测的高斯卷积，索贝尔operation.entire代码组成，是在建MATLAB函数任何自由，除了必须改变形象reading.threshold根据图像和被提取的特征。 做检查更新的高斯卷积文件，它比前一个准确 请注意，代码的执行时间是low.This是因为没有内在的功能被使用。 为了提高车速了，请改为内置的功能“conv2“的卷积码 -canny edge detection comprising of gaussian convolution,so
Matlab-program-gray-edge-detection
- 本文主要讨论获得图片后如何提取其边界信息，首先利用图像灰度均匀化解决了对比度不清晰的问题，然后利用高斯滤波法对图片进行滤波去噪，进而利用Canny算法实现边缘检测提取边界，该方法与Matlab自带的求边界方法有明显的提高，为利用Matlab程序求图像分形维数提供了更精确的前提。-This article focuses on how to get the image to extract the boundary information, the first to use to the gray
bianyuantiqu
- 基于matlab的边缘提取，边缘检测的一般算法包括Canny算子、Prewitt算子、Sobel算子、Roberts算子。-Matlab-based edge detection, edge detection algorithms, including general Canny operator, Prewitt operator, Sobel operator, Roberts operator.
bound2im
- 在MATLAB环境下对图像二值化处理后对图像进行edge的边缘提取，用于数值图像处理的相关领域中。-In the MATLAB environment on the image binarization edge of the image edge extraction, related fields for numerical image processing.
54351645
- 边缘提取和边缘检测matlab代码，可以参考下-Edge extraction and edge detection matlab code, you can refer to the following
laplacian
- 此文件是自己用matlab编的拉普拉斯算子进行图像边缘特征的提取-This file is used to extract their own matlab compiled Laplacian image edge features