Color SURF detector

Question

SURF by default works on Gray image. I am thinking to do SURF on HSV image. My method is to separate the channels into H, S and V. And I use S and V for keypoint detection. I tried to compare the number of keypoints in SV vs RGB and in terms of channel wise, HSV gives more features.

Not sure what I am doing is correct or not. Need some explanation of the possibility of applying SURF on HSV image. I have read a paper on applying SIFT on different color space but not SURF.

1. Is there better way to achieve this?
2. Can we apply SURF to color, HSV space?

Thank you for your time.

Answer 1

2. Can we apply SURF to color, HSV space?

I didn't test it, but as far as I know, SIFT and SURF use quite (in principle) similar detection techniques:

SIFT detector uses the Difference-of-Gaussian (DoG) technique to efficiently approximate the Laplacian-of-Gaussian (LoG), which both are Blob Detection techniques.

SURF detector uses box-filters/box-blurs of arbitrary size to compute (or approximate?) The determinant of the Hessian which is a Blob Detection technique.

Both methods use some strategy to compute those blobs in multiple scales (SIFT: DoG-Pyramid; SURF: integral images to scale the filter sizes). At the end, both methods detect blobs in the given 2D array.

So if SIFT can detect good features in your (H)SV channels, SURF should be able to do the same because in principle they both detect blobs. What you will do is detecting blobs in the hue/saturation/value channel:

• hue-blobs: regions of similar color-tone which are surrounded by different (all higher or all lower) color-tones;

• saturation-blobs: regions of... yea of what? no idea how to interpret that;

• value-blobs: should give very similar results to the grayimage converted RGB image's blobs.

One thing to add: I'm just handling the detector! No idea how SIFT/SURF description is influenced by color data.