The book embodies an in-depth study of Euclidean Distance Transform (EDT) of a binary image and its applications in the areas of Image Processing and Computer Vision. Main emphasis has been given for designing fast and parallel algorithm, which ideally suits for VLSI implementation specifically in Cellular Architectures. Earlier work in the field of distance transform and its applications has been reviewed along with their proposed VLSI architectures. Subsequently, an O(n) time parallel algorithm is developed for EDT of an nxn binary image and its implementation in a cellular architecture is presented. Based on sound EDT computation, efficient parallel algorithms have been developed for the computation of the skeleton of a binary image, construction of discrete Voronoi diagram of objects in an image and the computation of the Hausdorff distance between images. It is also shown that these algorithms are realizable in cellular architectures. Further, applications of Skeleton, Voronoi diagram and Hausdorff distance are also explored successfully in this book.