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Any other inputs?

Thank you.. I am not able to see this method under any class.. Can anybody give me a hand?

As per the link https://github.com/opencv/opencv/wiki...

i found that

"more efficient camera support on Android 5+ faster round() on ARM (it’s also applicable to iOS); big thanks to Manuele Tamburano and Stefano Fabri for this!"

Can anyone point me this method in opencv api documentation or the class where this method under?

Also, whats special with that method?

Is there any function there in OpenCV to do it?

If there is no function in OpenCV how can I implement it? any idea would be great..

The input will be an image and the output should be the blurriness and sharpness of the image.

I am developing an image processing application in Centos with OpenCV using C/C++ coding. My intension is to have a single development platform for Linux and IOS (IPAD). So if I start the development in a Linux environment with OpenCV installed ( in C/C++ ), can I use the same code in IOS without going for Objective-C? I don't want to put dual effort for iOS so how to achieve this?

I am converting a matlab code into C++ using OpenCV libraries.

Can anyone tell me roipoly matlab function equivalent in OpenCV??

Or how to get the same functionality using OpenCV?

BW = roipoly(I, c, r)

BW = roipoly(I, c, r) returns the ROI specified by the polygon described by vectors c and r, which specify the column and row indices of each vertex, respectively. c and r are of same size.

In my case I want to extract triangular roi from the image, so c and r are of size 3x1.

Can anyone tell me how to do this in C++ using OpenCV??

Hi I am new to image processing field. My project is to classify the objects in an image/Video. The input is an image/video from surveillance camera. I should classify the objects into three classes. 1) Humans 2) Animals 3) Others (cars). We can consider a fixed background.

Can any one suggest any proven algorithms or papers or opensource code for this purpose? offcourse googling is obvious solution but always an experienced eye is always helpful!

Project: Face Detection

Description: I want to detect and crop a face in an image. The image is captured through webcam and only one face per image.I used OpenCV face detector, but I was not satisfied with the cropping. So, I started using STASM (http://www.milbo.users.sonic.net/stasm/) face landmark detector to crop the image.STASM uses OpenCV face detector to find face in an image and STASM locates landmarks in faces. In bad light conditions, the cropped image from STASM is not good as it is not exactly detecting the face alone.

1) I want to know any better algorithm for face detection. My main aim is to crop the face from an image.

2) currently I am using STASM for cropping. In bad light conditions or when in an image, if the whole or complete face (forehead to chin) is not captured, STASM cropping is not reliable (The output will be only eye or lips). And in my application, if there is no proper output from the stasm or if the face is not cropped prpoerly then i should reject the images. How to do that? So I am planning to validate the face in an image by finding the Eyes. If I am right in my approach, how to detect the eyes from the cropped image?

My project is Face Authentication.

System Description: My input is only one image (which was taken when the user logins for the first time) and using that image system should authenticate whenever the user logins to the application. The authentication images may differ from the first input image like -- different illumination conditions, different distance from camera and -10 to 10 degrees variation in pose. The camera used is same (ex: ipad) for all cases.

1) Authentication images are stored each time the user logins. How to make use of these images to enhance the accuracy of the system??

2) When a new image comes, I need to select the closest image(s) (and not all stored images) from the image repository and use for authenticate to reduce the time. How to label an image based on illumination/distance from camera automatically??

3) How should I make my system to perform decently for changes in illumination and distance from camera??

Please, can anyone suggest me good alogirthm/papers/opensource-codes for my above questions??

Though it sounds like a research project, I would be extremely grateful if I get any response from someone.

I found Opencv2.4.3 get released, and experienced guys or people who already started working on this latest version can suggest me a stable version? Or is it good to go with the latest one? Am Planning to use this version both in Linux and Windows. Please post your suggestions..

Project: Red eye detection

Description: I want to remove red-eye from images. I am not able to use face detector because, the faces in the images are not always frontal and also the images are of players with helmet. And the images may have many red eyes. Also, the lighting is not proper. I want to know how to detect the red eyes? I am searching for some proven studies. Any help would be appreciated.

I know this is one of the most repeated questions, however, no working solution found anywhere, after putting so much of efforts.

This is really a killing issue though it might be a simple one for the experts.

I am working on opencv Haar Cascade classifiers.(Eg: Face Detection, Eye Pair Detection)

I have just taken the face-detection sample code from the "OpenCV-2.4.9-android-sdk" - samples.

This sample code is set in Landscape mode and everything is working fine.

However, i want to make make the classifiers work in portrait mode. I know the haar classifiers were not made to work with portrait mode.

As opencv uses "CameraBridgeViewBase", i don't have all controls to play with the resolution of the camera and displaying the images back on the screen.(preview)

Now, the moment i set the screen orientation as "android:screenOrientation="portrait", the images is rotated 90deg clock wise.

What have i tried:

To preview the portrait image without rotation: i modified the "deliverAndDrawFrame" in "CameraBridgeViewBase" by adding

            Matrix matrix = new Matrix();
            matrix.preTranslate((canvas.getWidth() - mCacheBitmap.getWidth()) / 2,(canvas.getHeight() - mCacheBitmap.getHeight()) / 2);

            if(getResources().getConfiguration().orientation == Configuration.ORIENTATION_PORTRAIT)
                matrix.postRotate(90f,(canvas.getWidth()) / 2,(canvas.getHeight()) / 2);
            canvas.drawBitmap(mCacheBitmap, matrix, null);

To make the classifier work with portrait mode: I played with all kinds of permutation and combination of transpose and flip to rotate the grey scale image that i pass to detectmultiscale in "onCameraFrame".

What is my issue?

1. I am not able to get the images with native resolution which is higher than what i get at "onCameraFrame". How to get the original or actual or native quality of the images upto the camera sensors capacity?

2. As i already put a lot efforts on making the classifier work with portrait mode without any luck, any kind of suggestions/sample codes/reference which are working,would help me a lot.