image-segmentation

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 image haven't decided yet) change color of the vehicle body apply tint colors to the vehicle windows

I'm working in project that basically I have to detect the threes on image and delete the other information. I used HSV as segmentation and the function regionprops to detect each element. It works fine, but in same cases that has house roofs, they aren't deleted because the value of Hue is similar to the threes. So far, this is the result: To remove the roofs, I thought that maybe is possible detecting the color green in each region detected. If the region dont have 70% of green (for example) that region is deleted. How can I do that? How Can I detect only the green color of the image?

I'm trying to identify the number of matches and coins of each value in a picture using MATLAB. Here is the starting picture, with matches and 4 different coin values. (5 small silver, 2 small gold, 2 big silver, 4 big gold coins) The output: Here's the code: close all; img = (imread('C:\Users\Torstein\Jottacloud\Skole\Visu\Prosjekt\sample_images\sample2.jpg')); img_gray = rgb2gray(img); % Filter image for easier edge detection m = 12; n = 12; img_filter = imfilter(img_gray, fspecial('average', [m n])); %figure, imshow(f), title('f') % Edge detection [~, threshold] = edge(img_filter, 'canny');

I am trying to use the vl_slic_segment function of the VLFeat library using an input image stored in an OpenCV Mat. My code is compiling and running, but the output superpixel values do not make sense. Here is my code so far : Mat bgrUChar = imread("/pathtowherever/image.jpg"); Mat bgrFloat; bgrUChar.convertTo(bgrFloat, CV_32FC3, 1.0/255); cv::Mat labFloat; cvtColor(bgrFloat, labFloat, CV_BGR2Lab); Mat labels(labFloat.size(), CV_32SC1); vl_slic_segment(labels.ptr<vl_uint32>(),labFloat.ptr<const float>(),labFloat.cols,labFloat.rows,labFloat.channels(),30,0.1,25); I have tried not converting it

I am training a U-Net in keras by minimizing the dice_loss function that is popularly used for this problem: adapted from here and here def dsc(y_true, y_pred): smooth = 1. y_true_f = K.flatten(y_true) y_pred_f = K.flatten(y_pred) intersection = K.sum(y_true_f * y_pred_f) score = (2. * intersection + smooth) / (K.sum(y_true_f) + K.sum(y_pred_f) + smooth) return score def dice_loss(y_true, y_pred): return (1 - dsc(y_true, y_pred)) This implementation is different from the traditional dice loss because it has a smoothing term to make it "differentiable". I just don't understand how adding the

I followed the 2-D Watershed example in Mathworks.com to separate the connected objects, like the image below: The code is summarize as: bw = imread('some_binary_image.tif'); D = -bwdist(~bw); D(~bw) = -Inf; L = watershed(D); The result is: The particle in the center has been separated into two. Are there any ways to avoid the over-segmentation here? Thanks, lennon310, chessboard does work well for most of my images, but there are still some cases that it doesn't. For example, the following binary image: Using chessboard will result in: As I have hundreds of images, it seems that it is

I have several binary images and my task is to segment circle-like shape. The circles are not perfect rounded circle, but all of them will look like circle. Here are some example images and what I need: As you can see from above, the left images are original images, and the right images are what I need to do. The circles intersect with other shapes, but I only want the circle, as indicated in red. The imaginary lines to close the circle will be required. What can I do in this case in Image Processing? EDIT: in case, the image above is broken, here: http://imageshack.us/photo/my-images/835