% Convert an image to the Lab color spacecolorTransform = makecform('srgb2lab'); img = applycform(rgbImg, colorTransform);% Make it double to improve representationimg = double(img);% Find x and y derivative of a 9x9 gaussian[hx, hy] = gradient(fspecial('gaussian',[99],sigma));%...
Fuzzy logic is a widely used tool in image processing since it gives very efficient result. We develop a fuzzy inference system in MATLAB in order to get a simple fuzzy rules based edge detection technique. The technique uses the ... B Bhagabati,C Das 被引量: 7发表: 2012年 Edge Detect...
A new edge detection procedure which calculates closed edges (grain boundaries) for images of petrographic thin sections is presented. Edges are extracted from a gradient image obtained using the rotating polarizer stage microscope. The gradient image is calculated by passing a simple gradient operator...
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Run the edge_detect program on an image of your choice (sample images provided in img/) Dependencies Linux CUDA GPGPU framework (nvcc) Magick++ image library The edge detection program uses the Magick++ library to read and write images of arbitrary encoding. The library also provides low-level...
梯度简单来说就是求导,OpenCV 提供了三种不同的梯度滤波器,或者说高通滤波器: Sobel,Scharr 和 Laplacian。 Sobel, Scharr 其实就是求一阶或二阶导数。 Scharr 是对 Sobel(使用小的卷积核求解求解梯度角度时)的优化。 Laplacian 是求二阶导数。 Sobel算子 cv2.Sobel() ...
in different depth simultaneously.The test of theoretical model indicates that this method could detect the geological edges in different depth and the result is in accordance with model edge.We applied this method to real data,compared with other edge detection methods,this method could recognize ...
We characterize the problem of detecting edges in images as a fuzzy reasoning problem. The edge detection problem is divided into three stages: filtering, detection, and tracing. Images are filtered by applying fuzzy reasoning based on local pixel characteristics to control the degree of Gaussian sm...
Figure 1. Edge Detection [1] Earlier works Edge Detection is a classical computer vision problem. There have been many algorithms in the past that have worked well, to a certain degree, for edge detection. Most of these employed well-researched filters or operators that worked in most cases....
Good Detection: The optimal detector must minimize the probability of false positives as well as false negatives.(大概是尽可能减少噪音的影响) Criterion 2: Good Localization: The edges detected must be as close as possible to the true edges.(更为准确的定位) ...