Color based tracking open cv

color based tracking open cv

Object detection and tracking is a field of computer vision that any object with a blue color from a webcam stream using OpenCV and CUDA. Preamble. I needed some color based object tracking for a project I was hacking together last weekend. I choose to use the OpenCV Python bindings since I. One simple method is color based tracking. I have developed a simple tool for that with OpenCV. All you have to do is just to adjust the High. Detection of a specific color(blue here) using OpenCV with Python . we know how to convert BGR image to HSV, we can use this to extract a colored object. Colour-based Object Detection and Tracking for Autonomous algorithms with the use of OpenCV video-processing library to quic ly process real time video. color based tracking open cv

If you're new to image processing, you'll enjoy this project. What we'll attempt to achieve in this tutorial is tracking the location of a coloured object in an image.

In our case, it'll be a yellow colored ball. Once we're finished, we'll have something like this: Looks great right? So lets dive right in! First, create a Win32 console application. Choose any name you like, and accept the default wizard options. You'll get an empty project with a main function. First, add these header files to the code:. Next, add the library files to the project. Before diving right into the code, its always a good idea to put a little insight into what we're doing.

Our program flow should go something like this:. To get an image from the camera, we'll use code from Capturing Imagesthat is, we'll use inbuilt Color based tracking open cv functions that let you access camera. For figuring out where the ball is, we'll first threshold the image and use zero order and first order moments.

To keep a track of where the ball has been, we'll use another image. We'll keep drawing wherever the ball goes, and combine this image with the original frame. That way, we'll get a "scribble" like effect.

You'll see what I mean when we implement it in code. This function will take an image, and return a binary image where yellow will be white and the rest will be black. Here's a sample of what might be a scenario:. In HSV, each "tint" of colour is assigned a particular number color based tracking open cv Hue.

The "amount" of colour is assigned another rakshana 1993 mp3 the Saturation and the brightness of the colour is assigned another number the Intensity or Value. This gives us the advantage of having a single number color based tracking open cv for the yellow ball despite multiple shades of yellow all the way from dark yellow to a bright yellow.

We keep the original image img intact, for future uses. Here, imgHSV is the reference image. And the two cvScalars represent the lower and upper bound of values that are yellowish in colour. These bounds should work in almost all conditions. If they don't, try experimenting with the last two values. Consider any pixel. If all three values of that pixel H, S and V, in initialiseren whatsapp order like within the stated ranges, imgThreshed gets a value of at that corresponding pixel.

This is color based tracking open cv for all pixels. So what you finally get is a thresholded image. First, we initialize the capturing device. If we don't get a device, we simply exit We'll keep updating imgScribble with appropriate lines.

And we'll add this image to the current frame. Here's a possible situation:. If you noticed, we just created imgScribble. We didn't allocate any memory to it.

The first frame would be a good place to do so. If the code reaches this far, we're sure that a frame was captured, and the imgScribble is a valid image. So we get down to business, and generate the thresholded image using the function we wrote above:. Now imgYellowThresh holds a binary image similar to the ones shown above. Now we use mathematics based calculations to figure out the position of the yellow ball.

I'm assuming that there will be only one yellow object on screen. If you have multiple objects, this code won't work. You first allocate memory to the moments structure, and then you calculate the various moments.

And then using the moments structure, you calculate the two first order moments moment10 and moment01 and the zeroth order moment area. Dividing moment10 by area gives the X coordinate of the yellow ball, and similarly, dividing moment01 by area gives the Y coordinate.

Now, we need some mechanism to be able to store the previous position. We do that using static variables:. The current position of the ball is stored in posX and posY, and the previous location is stored in lastX and lastY. We simply create a line from the previous point to the current point, of yellow colour and a width of 5 pixels. The if condition prevents any invalid points from being drawn on the screen.

Just try taking the yellow object out of the screen once color based tracking open cv program is done And finally, we release the thresholded image.

We don't want to accumulate multiple thresholded images If you want to try some different color, you'll have to figure out it's hue. There are two ways to do that. First - hit and trial. Go through all possible values and you'll hopefully end up getting a good value. The other method requires using some photo manipulation software MS Paint will do. Open the color selection palette. Go through the colors and you should see a text box labeled Hue. Go through all possible Hues to find the range of values.

For example, in MS Paint, it is But OpenCV's hue values range from Learn about the latest in AI technology with in-depth tutorials on vision and learning! Toggle navigation AI Shack. Tutorials About. Creating the project First, create a Win32 console application.

First, add these header files to the code: Throw an error and quit if! Utkarsh Sinha created AI Shack in and has since been working on computer vision and related fields. He is currently nooru janmaku karaoke mp3 Microsoft working on computer vision. Follow utkarshsinha. Get started Get started with OpenCV Track a specific color on video Learn basic image processing algorithms How to build artificial color based tracking open cv Look at some source code.

AI Shack. Created by Utkarsh Sinha.

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