edge-detection

问题 I am new on VHDL, I have a push button which I want to detect the it signal when it is pushed, meaning i want to detect the raising edge of the signal push button when it is pressed? I did research and all what I found was about the detecting the raising edge of a clk. the problem that I have is that when the push button is pressed the the signal for the push button goes to 1 and stay at 1 until until another even happen so I am interested more when the signal of the push button raise? 回答1:

问题 I am writing a computer vision library from scratch in Python to work with a rpi camera. At the moment, I have implemented conversion to greyscale and some other basic img operations which both run relatively fast on my model B rpi3 . However, my edge detection function using the sobel operator (wikipedia description) is much slower than the other functions although it does work. Here it is: def sobel(img): xKernel = np.array([[-1,0,1],[-2,0,2],[-1,0,1]]) yKernel = np.array([[-1,-2,-1],[0,0,0

问题 Here are some images taken from experiments which show a bubble caused by spheres moving in liquid. Now I want to get the area of the bubble from every image using Matlab. The first thing come to my mind is edge detection. So I tried using the following code: A = imread('D:\1.jpg'); BW1 = edge(A,'sobel'); figure, imshow(BW1) to get the cavity edge of the picture which was then cropped manually, as the picture show, the result (below) doesn't satisfy requirements. Also, I still don't know how

问题 For my final year project I'm doing a vehicle detail modification system. the system should be able to these following tasks. I'm using a size image of a vehicle taken from a fixed distance lets say from 5m. and different colors and rim images are stored I'm my application, that is is the basic idea. detect the tire and the alloy rim of the vehicle detect and measure the rim size of the installed rim apply a new alloy rim to the vehicle ( embed or put the alloy rim on top of the original

问题 In my app, I will input a human image and I want to get the face and neck only of that person as output in separate image. Example: Below image as input:(Source:http://www.fremantlepress.com.au) And I want to get the up image as output: I want to perform the following algorithm: 1. Detect face 2. Select (face region * 2) area 3. Detect skin and neck 4. Cut the skin region of the selected image 5. Save that cut region into a new image As going through the EmguCV wiki and other online resources

问题 Using images of articles of clothing taken against a consistent background, I would like to make all pixels in the image transparent except for the clothing. What is the best way to go about this? I have researched the algorithms that are common for this and the open source library opencv. Aside from rolling my own or using opencv is there an easy way to do this? I am open to any language or platform. Thanks 回答1: If your background is consistend in an image but inconsistent across images it

问题 Using images of articles of clothing taken against a consistent background, I would like to make all pixels in the image transparent except for the clothing. What is the best way to go about this? I have researched the algorithms that are common for this and the open source library opencv. Aside from rolling my own or using opencv is there an easy way to do this? I am open to any language or platform. Thanks 回答1: If your background is consistend in an image but inconsistent across images it

问题 I'm trying to write a ridge detection algorithm, and all of the sources I've found seem to conflate edge detection with ridge detection. Right now, I've implemented the Canny edge detection algorithm, but it's not what I want: for example, given a single line in the image, it will effectively translate it to a double line of edges (since it will record both sides of the line) - I just want it to read the one line. The wikipedia article about ridge detection has a bunch of math, but this kind

问题 I'm trying to apply the Sobel filter on an image to detect edges using scipy. I'm using Python 3.2 (64 bit) and scipy 0.9.0 on Windows 7 Ultimate (64 bit). Currently my code is as follows: import scipy from scipy import ndimage im = scipy.misc.imread('bike.jpg') processed = ndimage.sobel(im, 0) scipy.misc.imsave('sobel.jpg', processed) I don't know what I'm doing wrong, but the processed image does not look anything like what it should. The image, 'bike.jpg' is a greyscale (mode 'L' not 'RGB'

问题 I'm trying to implement SED from OpenCV to android but I'm running into an error. So this is the code I'm using and it requires a model file (trained model to detect edges) which is located in the asset folder : private Bitmap StructuredDetectEdges (Bitmap bitmap){ Mat rgba = new Mat(); Utils.bitmapToMat(bitmap,rgba); Mat edges = new Mat(rgba.size(), CvType.CV_8UC1); Imgproc.cvtColor(rgba,edges,Imgproc.COLOR_RGB2GRAY,4); StructuredEdgeDetection pDollar = createStructuredEdgeDetection("file://