#Chessboard pdf open cv face detection how to
#Chessboard pdf open cv face detection code

If you look at yours, you've got it the wrong way round: fx 0 0 If you read the documentation, it should look like: fx 0 cx I'm letting you write the function to find the largest square. Find contours and store them in a listДЇindContours(gray, contours, CV_RETR_LIST, CV_CHAIN_APPROX_SIMPLE) find squares in every color plane of the imageДЇor (int c = 0 c = (l+1) * 255 / threshold_level

#Chessboard pdf open cv face detection code

I made some modifications to the squares demo present in OpenCV and the resulting C++ code below is able to detect a sheet of paper in the image: void find_squares(Mat& image, vector >& squares) This is a recurring subject in Stackoverflow and since I was unable to find a relevant implementation I decided to accept the challenge. Maybe you could do an initial synchronize with the database so that the images are cached on the phone? One way or another I think you are probably going to have to have the images on the phone at some point regardless.ДЇiguring out the best way to store the recognition data/images in the database was one of the biggest challenges I faced so I would be interested to hear if you find a good method.

#Chessboard pdf open cv face detection how to

There is also the issue of how to expose the remote database to the application, however I do believe this is possible using PHP and JSON (and other technologies, see below).

You can compress the images however this may lead to a worse recognition rate, due to image quality reduction and also you will have to decode on the device. Once 1 and 2 have been completed the system is very quick as it just performs recognition against the training set.ДЇortunately for me, my database server was located on a LAN therefore speed wasn't a problem, however I can see why you have an issue due to the fact that on a mobile device you have a limited data connection (speed/bandwidth).Generate training set based on these images.Open application and grab training images from database.In my application, I would go through the following steps. The database is a particularly tricky part of the system as this is where the biggest bottleneck is. I stored all my images in the database as Blob data types then loaded them into my program when necessary. I actually did something similar to you albeit on a PC not an iPhone but its still the same concept. You could also look at implementing it yourself if you feel brave (it's not too bad). That link shows a tutorial on how to get that working with OpenCV - I think this is written for C but i'm sure you can get the basic jist of it. I would use a method such as Principal Component Analysis (PCA) a.k.a eigenfaces. I would use the Haarcascades available in open CV to perform quick and accurate face detection.