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Preprocess images before feature detection?

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Hi! My goal is to find known logos in static image and videos. I want to achieve that by using feature detecton with KAZE or AKAZE and RanSac. I am aiming for a similar result to: https://www.youtube.com/watch?v=nzrqHqB-dLM While experimenting with the [detection example from the docs](http://docs.opencv.org/3.1.0/d7/dff/tutorial_feature_homography.html#gsc.tab=0) which is great btw, i was facing several issues: - Object resolution: Differences in size between the known object and the resolution of the scene where the object should be located sometimes breaks the detection algorithm - the object won't be recognized in images with a low resolution although the image quality is still allright for a human eye. - Color contrast with the background: It seems, that the detection can easily be distracted by different background contrasts (eg: object is logo black on white background, logo in scene is white on black background). How can I make the detection more robust against different luminations and background contrasts? - Preprocessing: Should there be done any kind of preprocessing of the object / scene? For example enlarge the scene up to a specific size? Is there any guideline how to approach the feature detection in several steps to get the best results? Thanks a lot for your help! best, Manu

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