On convergence of hopfield neural networks for real time image matching
نویسندگان
چکیده
Present paper demonstrates on innovative approach for a fundamental problem in computer vision to map real time a pixel in one image to a pixel on another image of the same scene, which is generally called image correspondence problem. It is a novel real time image matching method which combines Rotational Invariant Feature Selection for real time images and optimization capabilities of Hopfield Neural Networks. The most invariant image matching features are extracted from the reference image. Finally, the image matching process is optimized by Hopfield neural networks, where image matching problem is treated as minimization of energy function of the Hopfield neural networks.
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