edge-detection

I have a picture contains blood smear. What I want to do is to detect the edges of those cells. I first convert this color image into grayscale image and then fill holes in those cells. And I use the edge() function in matlab to detect edges. Since you can observe the inner part of some cell is much lighter, so there are edges detected inside one cell. The result is shown below: So is there any methods that only the outer edges of those cells can be detected? My code is shown below: I = imread('film02_pattern.jpg'); t1=graythresh(I); k1=im2bw(I,t1); k1=~k1; se = strel('disk',1); k1=imfill(k1,

I have written algorithm to extract the points shown in the image. They form convex shape and I know order of them. How do I extract corners (top 3 and bottom 3) from such points? I'm using opencv. HugoRune if you already have the convex hull of the object, and that hull includes the corner points, then all you need to to do is simplify the hull until it only has 6 points. There are many ways to simplify polygons, for example you could just use this simple algorithm used in this answer: How to find corner coordinates of a rectangle in an image do for each point P on the convex hull: measure

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

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, I am confident to perform the step 1 and 2. But I am not sure how can I accomplish step 3 and 4.

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 If your background is consistend in an image but inconsistent across images it could get tricky, but here is what I would do: Separate the image into some intensity/colour form such as

I am trying to make a computer vision program in which it would detect litter and random trash in a noisy background such as the beach (noisy due to sand). Original Image: Canny Edge detection without any image processing: I realize that a certain combination of image processing technique will help me accomplish my goal of ignoring the noisy sandy background and detect all trash and objects on the ground. I tried to preform median blurring, play around and tune the parameters, and it gave me this: It preforms well in terms of ignoring the sandy background, but it fails to detect some of the

I am working on the project and part of it is to recognize objects recorded on camera. So to be more specofic: I am using OpenCV I have correctly setup camera and am able to retrieve pictures from it I have compiled and experimented with number of demos from OpenCV I need a scale- AND rotation- invariant algorithm for detection Pictures of original objects are ONLY available as edge-images All feature detection/extraction/matching algorithms I have seen so far are working reasonably well with gray-scale images (like photos), however due to my project specs I need to work with edge images

I am able to detect the largest square/rectangle (in green) in an image. However, I want to convert the largest square/rectangle detected in the image into a new image (to be stored in a new Mat). Here's the return image of this function that has the largest rectangle/square on it: http://img153.imageshack.us/img153/9308/nn4w.png Here is my code so far: private Mat findLargestRectangle(Mat original_image) { Mat imgSource = original_image; //convert the image to black and white Imgproc.cvtColor(imgSource, imgSource, Imgproc.COLOR_BGR2GRAY); //convert the image to black and white does (8 bit)