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    <p>There is no keypoint in your image...</p> <p>Why ?</p> <ul> <li>Because there is no keypoint in a uniform color plane (why would there be ? as it is uniform nothing is an highlight)</li> <li>Because everything is symmetric in your image, it wouldn't really help to have keypoints, according to certain feature extractor they would have the same feature vectors</li> <li>Because there's no corner or high gradient in cross directions which would result in keypoints fro many feature detectors</li> </ul> <p>What you could try is a template matching method if you are searching for this logo without big changes (rotation, translation, noise etc) a simple correlation is the easiiiiest.</p> <p>If you want to go further, one of my idea, that I have never implemented but which could be funny : would be to have sets of this image that you scale, rotate, warp, desaturate, increase noise with functions and then apply template matching with this set of images you got from your former template... Well this idea comes from SIFT and Wavelet transform, where we use sort of functions that we change in some ways (rotation, noise, frequency etc...) in order to give robustness to our transform against these basic changes that occur in any image that you want to "inspect". That could be an idea for you !</p> <p><img src="https://i.stack.imgur.com/gYQPZ.png" alt="enter image description here"></p> <p>Here is an image summarizing my idea, you rotate and scale your template, actually it creates a new rotated/scaled template that you can try to match, it will increase robustness (even if it can be very long if you choose a lot of parameters to change). Well i'm not saying that's an algorithm, but it could be a funny and very basic idea to try...</p> <p>Julien,</p>
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