Any advice on how to acheive vowel detection using WebAudio?
I assume somthing with analyser.getFloatFrequencyData
Hoping someone may have some insight.
Related
Hi we are trying to find out what are the minimal requirements for a graph to be able to solve the hanoi problem.
Where the vertex are the pegs, and each edge represent a possible movement from one peg to another.
So basicly its Hanoi problem with restrictions that tell us what are our possible moves.
There can be any number of pegs and any number of discs.
So far we found that we need a strongly connected graph. but there is no explanation why.
If anyone can shed some light on the subject it will be appreciated, thank you!
Hi I have been searching though research papers on what features would be good for me to use in my handwritten OCR classifying neural network. I am a beginner so I have been just taking the image of the handwritten character, made a bounding box around it, and then resize it into a 15x20 binary image. So this means i have an input layer of 300 features. From the papers i have found on google (most of which are quite old) the methods really vary. My accuracy is not bad with just a binary grid of the image, but I was wondering if anyone had other features I could use to boost my accuracy. Or even just pointing me in the right direction. I would really appreciate it!
Thanks,
Zach
I haven't read any actual papers on this topic, but my advice would be to get creative. Use anything you could think of that might help the classifier identify numbers.
My first thought would be to try and identify "lines" in the image, maybe via a modified "sliding window" algorithm (sliding/rotating line?), or to try and identify a "line of best fit" to the image (to help the classifier respond to changes in italicism or writing style). Really though, if you're using a neural network, it should be picking up on these sorts of things without your manual help (that's the whole point of them!)
I would focus first on the structure and topology of your net to try and improve performance, and worry about additional features only if you cannot get satisfactory performance some other way. Also you could try improving the features you already have, make sure the character is centered in the image, maybe try an algorithm to skew italicised characters to make them vertical?
In my experience these sorts of things don't often help, but you could get lucky and run into one that improves your net :)
I am just doing some research into image processing and would appreciate it if someone could point me in the right direction. I want to compare image 'A' which is a picture of a person's face with image's stored in a database -B,C,D,E .. etc which are also pictures of faces. I want to compare them to see if the person 'A' is already in the database.
Several questions :
1.How is face recognition comparison usually done? (do you extract features e.g. eyes/mouth and compare them to other images?).
2. Are there prebuilt libraries that are able to do a comparison between images? or do i need to write my own algorithm?
3. Where can i start with this? (would appreciate some references/reading material).
Yes, you identify, extract and quantify various aspects of human faces, such as distance between pupils, width of mouth, percentage of head height where tip of nose is, etc.
There is a company, Luxand which makes software to do this, and I think they license it. Last time I looked (2009?) they didn't have an objective-c library. They do have an app that claims to merge faces from photograhs, so you can see what the offspring of any two people would look like, but it is very cheesy, with lots of hard-coded faces. (If you cross a dog with a tea-pot, you get the same baby-face as from crossing a 2 real faces.)
AFAIK, there is nothing in the iOS SDK that does this.
I would just Google "face recognition" and start reading. Good luck.
I would go with compiling openCV for the iPhone ( http://computer-vision-talks.com/2011/02/building-opencv-for-iphone-in-one-click/ ), and then implementing one of the classical ways to do face recognition like eigenfaces ( http://www.shervinemami.info/faceRecognition.html )
But don't expect miracles the accuracy will be low, and the app will be slow.
Also when you say face recognition is difficult doesn't the first link show how easy it is to detect faces on a picture?
The face detection from the first link is just to detect the face. It is just to see if there is a face in the image, which then you can pass as input to the recognition algorithm.
face recognition are very difficult, you need to extract some kind of "features" and perform some measurement...iphone hardware isn't very appropriate for this job.
yes, you can check here
http://maniacdev.com/2011/11/tutorial-easy-face-detection-with-core-image-in-ios-5/
for a tutorial and here
http://maniacdev.com/2011/12/open-source-library-for-adding-easy-face-to-your-ios-app-with-the-free-face-com-api/
for a free webservice.
3.i suggest you google scholar (http://scholar.google.it/scholar?q=face+recognition&hl=it&btnG=Cerca&lr=) but i think that if you want to write your own algorithm you need a lot o spare time :)
I would like to start on Chinese hand-writing recognition program for IPhone...but I couldn't find any library or API that can help me to do so. It's hard for me to write the algorithm myself because of my time span.
Some of suggestion recommended that I should make use of a back-end server to do the recognition work. But I don't know how to set up that kind of server.
So any suggestion or basic steps that can help me to achieve this personal project?
You might want to check out Zinnia. Tegaki relies on other APIs (Zinnia is one of them) to do the actual character recognition.
I haven't looked at the code, but I gather it's written in C or C++, so should suit your needs better than Tegaki.
I have a small UIImage (jpg) with a single typed number. I want to be able to read the number with some kind of pattern recognition. I'm really not sure where to start, so any help would be appreciated.
my initial idea was to compare this image with other images. For instance compare the image with that of a 1,2,3, etc until a match was found. That just seems slow and cumbersome and wondered if there was a better way to do it?
Thanks
Update - I'm trying to convert sudoku puzzles from newspaper print to interactive puzzles
No, you are right, it will be slow and cumbersome. But on the plus side you don't have to write it yourself
http://sourceforge.net/projects/opencvlibrary/
Still not exactly easy tho, and i'm not sure about licensing, so… you don't mention why you need to do this (sounds a little odd).
Maybe you can avoid it? If you know the images are numerical digits 0-9, is there another way to track which one a particalur images is, apart from the way it's pixels are arranged?
Sorry if that sounds like i'm missing the point… Maybe you could fill in a few more details?
I read this really good write-up about this exact problem here: http://sudokugrab.blogspot.com/2009/07/how-does-it-all-work.html
It doesn't have any code samples, but explains the concepts, and might be able to point you in the right direction.
The following tutorial may be right down your alley:
http://blog.damiles.com/2008/11/basic-ocr-in-opencv/
It is a simple tutorial on doing number recognition and comes with the source code also.
Additionally, you may want to do a search on OCR SDK (Optical Character Recognition Software Development Kit). You will surely find a stack of them. Commercial ones a pricey though.
I would go for a "role your own" approach along the line of the OpenCV tutorial, especially since you are only interested in numbers.
All of the best ':-)