pats's profile - activity

Yes, I have done Ratio test with 0.8 threshold. In all these cases

Thank you for the help. I am bit new to this area, so I am not sure about the ratio test. This is the algo I used. https://github.com/pablofdezalc/kaze/blob/master/src/kaze_match.cpp, I tried GFTTDetector with default parameters. Did not give good fit. It's very very fast though. GFTTDetector fastCPU = new GFTTDetector(1000,0.01,1,3, true,0.04);

BRISK and BRIEF didn't do much different with FAST. I am bit new to this field, I am not sure about ratio test. This is the algo I used, which corresponds to OpenCV example. Thank you http://www.emgu.com/wiki/index.php/FAST_feature_detector_in_CSharp

Thanks for your response. I have updated the post with Kaze now. However the issue is time consumed. On a highend PC, it takes around 3 mins to compile this static Image. I want to run this in a phone if possible. Any idea why its taking this long.

Is this available on Open CV. ? Is it possible to find executable from some where?

I used several methods to extract features and then identified the card in the right in other images.

The results of (ORB+FREAK),(FAST + FREAK) and SIFT is as follows. The question is how do I improve first two methods to achieve the results of SIFT. Or what can I use in a commercial product, which gives good results

FAST settings FastDetector fastCPU = new FastDetector(10, true); Freak descriptor = new Freak(true, true, 22.0f, 4);

ORB settings ORBDetector descriptor = new ORBDetector(400); Freak descriptor = new Freak(true, true, 22.0f, 4);

KAZE

Thanks for the response. The image you see above is after using SIFT and homography on a bigger image comparing the bigger Image with ref image (i.e. the method shown in that URL). However, it did not exclude the fingers. homography matrix included the fingers. To provide more info. The finger could be any edge of the image. And it could be any finger (Most likely Thumb and index finger). However, more than 90% of the back side of the card will be visible.

Hi All,

Please see the image Below. A part of an image has been replaced by Ace of spade image. I want to figure out away to match the colors and contrast so that it looks real to some extent. (please ignore the miss alignment of the replacement in the image, assume it has been replaced precisely.)

The replaced image will only have Black and white color ranges, which I think would be a unique attribute.

Is there away to map image colors and contrast? Any special ways I can shoot the image being replaced?

Any other way I can do this. Given that the colors of the card and color of the finger is always different. And color of the card known before hand. However, the birgthness and contrast can vary

Thank you for your response. I used (http://www.academia.edu/4609424/Skin_Detection_using_HSV_color_space) and tried what you said. It identified part of the skin. But didn't identify the Nails. In my case, I always have the fingers, with nail part. Because the objective is to identify the card part of the image and replace it a different card preserving the fingers on top.

Can we use image difference techniques , since I have a card Image without fingers.

Thanks

Please see the Image below. As you can see it has a part of finger (bottom-right). How do I to some extent Identify it and color it black. That is retain the rest of image but remove in different part in the image.

I have the image with the card without finger as well. Which can be placed in a same size image in the same location.

What would be the approach and what functions can I use.

Thank you Regards Pati