image-processing

问题 I have a (540, 960, 1) shaped image with values ranging from [0..255] which is black and white. I need to convert it to a "heatmap" representation. As an example, pixels with 255 should be of most heat and pixels with 0 should be with least heat. Others in-between. I also need to return the heat maps as Numpy arrays so I can later merge them to a video. Is there a way to achieve this? 回答1: You need to convert the image to a proper grayscale representation. This can be done a few ways,

问题 In literature on digital image processing you find examples of Laplace kernels of relatively low orders, typically, 3 or 5. I wonder, is there any general way to build Laplace kernels or arbitrary order? Links or/and references would be appreciated. 回答1: The Laplace operator is defined as the sum of the second derivatives along each of the axes of the image. (That is, it is the trace of the Hessian matrix): ∇ I = ( ∂ 2 /∂ x 2 + ∂ 2 /∂ y 2 ) I There are two common ways to discretize this: Use

问题 In literature on digital image processing you find examples of Laplace kernels of relatively low orders, typically, 3 or 5. I wonder, is there any general way to build Laplace kernels or arbitrary order? Links or/and references would be appreciated. 回答1: The Laplace operator is defined as the sum of the second derivatives along each of the axes of the image. (That is, it is the trace of the Hessian matrix): ∇ I = ( ∂ 2 /∂ x 2 + ∂ 2 /∂ y 2 ) I There are two common ways to discretize this: Use

问题 I'm working an image analyzation project that checks the rgb values at set locations in a host of images, and need to be able to know if a certain area is green or blue. Originally I thought I could do this by testing if g>b in the rgb, but I've come to realize that often there can be more blue than green in a green image, due to the mixture with red. How can I tell- possibly a formula or an algorithm, what a color visibly appears to be based on the rgb? 回答1: You can convert RGB values to HSB

问题 I have masks of imperfect circle like this one. How can I use opencv contour function (or any other way) to remove the artifacts in the top-right corner? Here is the data,: mask = np.array([ [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,255,255], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,255,255], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,255,255,255,255,255,255,255,255,0,0,0,0,0,0,0,0,0,0,255,255,255], [0,0,0,0,0,0,0,0,0,0,0,0,255,255,255,255,255,255,255,255

问题 I am trying to identify paragraphs of text in a .pdf document by first converting it into an image then using OpenCV. But I am getting bounding boxes on lines of text instead of paragraphs. How can I set some threshold or some other limit to get paragraphs instead of lines? Here is the sample input image: Here is the output I am getting for the above sample: I am trying to get a single bounding box on the paragraph in the middle. I am using this code. import cv2 import numpy as np large = cv2

问题 I am trying to identify paragraphs of text in a .pdf document by first converting it into an image then using OpenCV. But I am getting bounding boxes on lines of text instead of paragraphs. How can I set some threshold or some other limit to get paragraphs instead of lines? Here is the sample input image: Here is the output I am getting for the above sample: I am trying to get a single bounding box on the paragraph in the middle. I am using this code. import cv2 import numpy as np large = cv2

问题 Below is my code , which is running fine but after a long processing it show me the run time error // Initialize constant values const int nb_cars = files.size(); const int not_cars = files_no.size(); const int num_img = nb_cars + not_cars; // Get the number of images // Initialize your training set. cv::Mat training_mat(num_img,dictionarySize,CV_32FC1); cv::Mat labels(0,1,CV_32FC1); std::vector<string> all_names; all_names.assign(files.begin(),files.end()); all_names.insert(all_names.end(),

问题 So I'm trying to get a sattelite map of my township that is available for offline use, and I used Universal Maps Downloader to download from bing's hybrid maps. That all worked fine, but when I used the program's built in image stitcher, I found that the resulting bitmap image was so large that it isn't a usable bitmap. Photoshop and all image viewers I can get my hands on won't view it (I'm guessing because bitmaps aren't supposed to be 6gb in size) So I'm wondering if A.) there are any

问题 In the process of image encryption using AES, when the pixel values are read and when the AES encryption applied, the cipher text results in some negative values. How is it possible to frame an encrypted image from these kind of negative values i.e., cipher text? 来源： https://stackoverflow.com/questions/33776494/how-to-write-aes-cipher-text-to-an-image