I would like to filter an image to make it more clear/sharper. What would be the best filter method for this in OpenCV?
If you want to sharpen the image this question might help you.
And for noise reduction here I have found an interesting article.
Filtering is a very broad topic and "make it more clear" is a rather vague objective. OpenCV has a number of filters implemented for you to try, and they are documented fairly extensively. If you are wanting more detailed advice, perhaps you should show some example images and explain what specifically you want to improve about them.
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I am working on image classification problem. How to find out specific features from the image manually that will help to build a DNN? Consider an image of a man talking on phone while driving for classification as distracted.
You don't do this. Having a good feature extractor is why we take DNNs in the first place
Also: you forgot to look to https://www.kaggle.com/c/state-farm-distracted-driver-detection
I am trying to Code a genetic algorithm in Matlab but really dont know how it works in images and how to proceed? Is there any basic tutorial that can help me understand how to apply GA on images (starting from 2d to multidimentional images ).
That will be a great help for me.
Thanking everyone in anticipations.
Kind Regards.
For GA you need two things: a fitness function that can evaluate any solution and tell how good it is, and a representation of your solution so that you can do crossover and mutation. Once you have these, you are good to go. I'm not an expert on image processing so I can't help you with that exactly.
Look at the book Essentials of metaheuristics which is a very good resource for start with evolutionary computation (and not only that) in general. It's free.
There is a paper on this subject which you can find at the IEEE library. I believe it solves the problem you vaguely describe.
I would like to know more about Gabor 1D and 2D kernels.
I am a newbie to the field of image processing.
When I search for this question in google, It throws up a lot of results, but all those links including those of wikipedia`s is not suited for beginners like me.
Kindly suggest some links to articles especially for BEGINNERS.
or even better,
It would be great if someone can give a detailed explaination to Gabor Filters for BEGINNERS.
Thanks in advance.
I want to train a new haar-cascade for glasses as I'm not satisfied with the results I'm getting from the cascade that is included in OpenCV.
My main problem is that I'm not sure where to get eyeglasses images. I can manually search and download, but that's not practical for the amount of images I really need. I'm specifically looking for images of people wearing eyeglasses.
As this forum contain many experienced computer vision experts, I hope someone here can guide as to how to obtain images for training.
I'll also be happy to hear other approaches for detecting eyeglasses (on people).
Thanks in advance,
Gil
If you simply want images, it looks like #herhuyongtao pointed you to a good place. Then you can follow opencv's tutorial on training.
Another option is to see what others have trained:
There's a trained data set found here that might be of use, which states simply that it is "better". I'm assuming that it's supposed to be better than opencv.
I didn't immediately see any other places for trained or labeled data.
I'm trying to cluster a really large dataset - 3030764x162 into 4000 clusters using the cvKmeans2 function in OpenCV 2.1.
I would like to see which iteration the K-means algorithm is currently in (similar to what is displayed in Matlab), but I don't see any documentation that points to how I can do this.
It's kind of frustrating seeing a blank screen and not knowing when the code is going to terminate!
Thank you.
Unfortunate as it seems, the answer is No, you cannot. There are no debugging/informative statements anywhere in the kmeans function as provided by OpenCV. However, you may edit and add statements to the method as you deem appropriate.
#Sau,
May be you need some other way of doing it. Though my answer is not relevant to OpenCV.
I have not tried in OpenCV, I had once done KMeans clustering for a extremely large data set and it was more a option better than OpenCV as it worked in a distributed mode. Though very lengthy, but still you might be interested. Its Kmeans clustering using Mahout
Check it out