Rezumat articol ediţie STUDIA UNIVERSITATIS BABEŞ-BOLYAI

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The distance transform is a mathematical operator with a wide range of applications in computer vision. In the state-of-the art the mostly discussed distance transform is the Euclidean distance transform of binary images. In this paper we propose an algorithm for general distance transform of sampled functions. In our method the only restriction is that the defined distance has to be an increasing function for each component. The proposed algorithm is compared with the low parabolas algorithm which is one of the most performant. Experimental results show advantages in computation speed even for the Euclidean distance transform of high resolution images. The most important property of our method is the usability for any kind of distances.

Key words and phrases. general distance transform, Euclidean distance transform, binary search tree, sampled functions.