I need to implement contours detection function in my iOS game, which I'm writing using cocos2d 2.1
For example user will provide me an image(PNG transparent):
So, I need detect shape polygon points and create box2d body from them, and I will able to put this image to my box2d scene.
I expect to have on output NSMutableArray with arrays of points of each polygon detected on the image.
Same do PhysicsEditor, here is result of it:
Here is also result using VertexHelper(shows wrong way of detection, as one polygon... ):
Also SpriteHelper but without detection of other parts of image
My question is: how can I do this? What way is better and faster?
I was looking for a solution in google, however I can't find any that will fit my needs...
I guess you are looking for a Sobel edge detection filter. Check out the GPUImage framework created by Brad Larson. It has an implementation of Sobel edge detection filter using objective-C which might be useful for you.
Finally done this by using Chipmunk Autogeometry feature. Work like a charm.
Just using https://github.com/slembcke/ConcaveSprite/blob/master/ConcaveSprite/ConcaveSprite.m I've saved my time...
Related
I am not an ios developer but my client wants me to make an iphone app like
https://itunes.apple.com/us/app/trippy-booth-amazing-filterswarps/id448037560?mt=8
I have seen some custom library like
https://github.com/BradLarson/GPUImage
but do not find any camera lens customization example.
any kind of suggestions would be helpful
Thanks in advance
You can do it through some custom shader written in OpenGL(or metal just for iOS), then you can apply your shader to do interesting stuff like the image in above link.
I suggest you take a look at how to use the OpenGL framework in iOS.
Basically the flow would like:
Use whatever framework to capture(even in real time) a image.
Use some framework to modify the image. (The magic occur here)
Use another stuff to present the image.
You should learn how to obtain a OpenGL context, draw a image on it, write a custom shader, apply the shader, get the output, to "distort the image". For real, the hardest part is how to create that "effect" in your mind by describing it using a formula.
This is quite similar to the photoshop mesh warp (Edit->Transform->Warp). Basically you treat your image as a texture and then you render it on to a mesh (Bezier Patch) that is a grid that has been distorted into bezier curves, but you leave the texture coordinates as if it was still a grid. This has the effect of "pulling" the image towards the nodes of the patch. You can use OpenGL (GL_PATCHES) for this; I imagine metal or sceneKit might work as well.
I can't tell from the screen shots but its possible that the examples you reference are actually placing their mesh based on facial recognition. CoreImage has basic facial recognition to give youth out and eye positions which you could use to control some of the nodes in your mesh.
I'm trying to detect an object composed of other objects. Actualy, there are three circles in my binary image which shape up a triangle as shown here:
These circles are correctly detected, but only as single objects as shown here:
What I need to have is an aggregation or composition of these objects, so they get detected as one big object as shown here:
The bigger goal is to get the image moments to get the rotation and scale of the shape. Please share your ideas or code if you have any, it would be well appreciated.
I would suggest using the bounding box functions of opencv
Here is a link to an example of bounding box in C++ OpenCV, however if you are using something like Python, it might be worth your while looking at this link, which is a full set of tutorials for working with binary images and contours (including bounding box/elipse)
Again if you are using the Python port, look at this set of tutorials, they really are great and have a massive supply of information on most functions of OpenCV.
Hope this helps.
Good luck.
Your question is very similar to this question, which has answers with code examples. Alternatively check the documentation of OpenCV. If you are interested in the convex hull of your points, see cv::convexHull().
I have to make a bot which has to overcome obstacles autonomously in an arena that will be filled with rocks. The bot has to find its way through this area and reach the end point. I am thinking of using edge detector operators like canny and sobel for this problem.
I want to know whether those will be suitable options for this problem. If so, then after detecting the edges, how can I make the bot find the path, overcoming the rock obstacles?
I am using QT IDE and opencv library.
Since you will be analyzing frames of video, and the robot will be moving most of the time, image differences and optical flow too will be helpful. Edge detection alone might not help a lot, unless the surroundings and obstacles are simple and have known properties. Posting a photo of the scene can help those who want to answer the question.
Yes, canny is a very good edge detector. In fact the opencv implementation uses sobel to get the gradient estimate. You may need to apply a Gaussian filter to the image before edge detection. Edges are good features to look for rocks, but depending on the background other features such as color may also be useful. It probably would be easier if you gather 3D scene information via stereo, or laser scanner, or kinect like sensor. Also consider detecting when you bump into rocks and building up a map of where they are.
You can use contours to detect any object. You can estimate its size by finding the area of the contours. Then you can use moments to find the center of the object.
did somebody tried to find a pizzamarker like this one with "only" OpenCV so far?
I was trying to detect this one but couldn't get good results so far. I do not know where this marker is in picture (no ROI is possible), the marker will be somewhere in the room (different ligthning effects) and not faceing orthoonal towards us. What I want - the corners and later the orientation of this marker extracted with the corners but first of all only the 5Corners. (up, down, left, right, center)
I was trying so far: threshold, noiseclearing, find contours but nothing realy helped for a good result. Chessboards or square markers are normaly found because of their (parallel) lines- i guess this can't help me here...
What is an easy way to find those markers?
How would you start?
Use other colorformat like HSV?
A step-by-step idea or tutorial would be realy helpfull. Cause i couldn't find tuts at the net. Maybe this marker isn't called pizzamarker -> does somebody knows the real name?
thx for help
First - thank you for all of your help.
It seems that several methods are usefull. Some more or less time expansive.
For me it was the easiest with a template matching but not with the same marker.
I used only a small part of it...
this can be found 5 times(4 times negative and one positive) in this new marker:
now I use only the 4 most negatives Points and the most positive and got my 5 points that I finaly wanted. To make this more sure, I check if they are close to each other and will do a cornerSubPix().
If you need something which can operate in real-time I'd go down the edge detection route and look for intersecting lines like these guys did. Seems fast and robust to lighting changes.
Read up on the Hough Line Transform in openCV to get started.
Addendum:
Black to White is the strongest edge you can have. If you create a gradient image and use the strongest edges found in the scene (via histogram or other) you will be able to limit the detection to only the black/white edges. Look for intersections. This should give you a small number of center points to apply Hough ellipse detection (or alternate) to. You could rotate in a template as a further check if you wish.
BTW.. OpenCV has Edge Detection, Hough transform and FitEllipse if you do go down this route.
actually this 'pizza' pattern is one of the building blocks of the haar featured used in the
Viola–Jones object detection framework.
So what I would do is compute the summed area table, or integral image using cv::integral(img) and then run exhaustive search for this pattern, on various scales (size dependant).
In each window you are using only 9 points (top-left, top-center, ..., bottom left).
You can train and use cvHaarDetectObjects to detect the marker using VJ.
Probably not the fastest method but it should work.
You can find more info on object detection methods using OpenCV here: http://opencv.willowgarage.com/documentation/object_detection.html
I want to make an apps detect an square/rectangle in my webcam using EMGU CV (an OPENCV wrapper). The square/rectangle will have a solid color.
if it's posible I would like to obtain the width and heigth of the square/rectangle
In this video you can see what I would like to do.
http://www.youtube.com/watch?v=ytvO2dijZ7A&NR=1
I'm working with C#
If you already know the color of the desired object then you can segment the image based on that color. (Which may be why the rectangle disapears when the guy movies the direction to and away from the camera [differences in lighting]. Once you have the object segmented out of the image you can do region calculations on the image. [In matlab think regionprops]
Once you have the blob you can attempt to do model fitting to get a good approximation of the object being represented.
In the video link provided what is probably being done is Surf feature detection. Take a look at the SURFFeture example that ships with EMGU. Rather than drawing lines in this case however the four corner points are detected and a shape drawn on top. Similar examples which will help you are ShapeDetection and TrafficSignRecognition both in the EMGU.CV.Examples folder. ShapeDetection will teach you how to classify the square and the StopSignDetector.cs class will show you another example of how to apply a surf feature detection algorithm.
It will require a little reconfiguration but if you get stuck feel free to ask another question.
Cheers
Chris