simba1382's profile - activity

Thanks, I did already try some methods to be honestly, histogram is pointless since the ponies (as you can see in the examples) are grayscale (plus the filter, of course). I never heard of ORB, FREAK and BRIEF, though, and I'm gonna try them and see if I get some result.

Thanks.

I am looking to compare a new image to a database of images, and then output the higher "similarity". The images I want to compare are similar, but the problem is though because they're not pixel by pixel equal. I've tried to use BoW (Bag Of Words) model already, as per recommendation, I tried various implementations without success, the best correct rate I got was 30%, which is something really low.

Let me show you what I am talking about: imgur gallery with 5 example images. I want to detect that the four initial images are equal, and the fifth one is different. I wouldn't mind only detecting that the ones with the same angle orientation are equal, though. (In my example 2, 3 and 4)

So, that being said, are there any better methods than BoW for that? Or perhaps BoW should be enough if I implemented in a different way?

Thanks in advance.

Thanks a LOT, you actually gave me some hope with this message! I had almost given up already, a learning based approach is EXACTLY what I want. Both links you sent me are done in MatLab (Which I'm familiar with, so that's actually good!), that being said do you recommend simply continuing with Matlab or actually swtiching to OpenCV? for performance purposes, that is.

Im not yet an Open CV user, Ive been using Matlab but Ive kept an eye in OpenCV for a while already. That being said, I would like to know if its even possible to implement one idea I had for a pet project of mine, before delving deep into openCV and really learning the language.

My goal is to compare images (They`re going to have noise) with a database of images, and tell me if it finds a match. For instance:img1 img2

How would I even tell they're both similar? Are there algorithms I can implement to tell me that?

I suppose I should use some sort of noise reduction/edge detection first (I already tried some and had success with edge detection, actually). So, assuming I have a decent edge detection, how could I compare them?

Thanks in advance

Thanks a lot, I actually was able to apply your very explained answer quickly and learn a lot from it. Thanks for everything!

I have been trying to do that:

http://prntscr.com/umv66 -> http://goo.gl/Bgmv2 (You can ignore the red lines, I just added them to illustrate the final objective)

So, what I've done in the first case was: Using MatLab, I transformed rgb -> hsv and picked up the s channel (a.k.a saturation). Then I used Otsu (called graythresh in matlab) to binarize and transform into a black and white picture. Everything worked perfectly.

Now, in the second case this doesn't work so well:

Base img(http://goo.gl/OtK4G) -> S Channel(http://goo.gl/oo8h6) ->Otsu(http://goo.gl/cnfxU)

As you can see, the Otsu filter becomes useless in this case. Is there any workaround or other way I should be taking? Thanks in advance!

Thanks a lot for this link, truly amazing expalanation. I'm going to test the suggestions you made me right now and see what I can learn from them.

I applied a few filters to make it harder (Since I knew how to solve a 'clean' labyrinth), the object was making the machine confused, it can't so easily determine what is path and what is wall.

Hello, I'm trying to do a project with some of my friends, and we came upon that:

Say I had to decipher this Labyrinth programatically, how could I go on about that? My first decision when trying to solve labyrinths by image recognition is obviously simply painting the open path, this way the paint end (The arrow in the start of the labyrinth is there to provide a way for the recognition to see 'ok that's the start')would indicate the exit.

Problem is, with those filters in place, I can't paint it, nor I have any other idea on how to solve it. So, would there be any way of doing so with Open CV? (or any other option would be fine too, if possible)

Thanks!