This chapter addresses various aspects of block matching. They include the concept and algorithm, matching criteria, searching strategies, limitations, and new improvements. An image is partitioned into a set of nonoverlapped, equally spaced, fixed size, small rectangular blocks; and the translation motion within each block is assumed to be uniform. Although this simple model considers only translation motion, other types of motions, such as rotation and zooming of large objects, may be closely approximated by the piecewise translation of these small blocks provided that these blocks are small enough. Block matching belongs to image matching and can be viewed from a wider perspective. In many image processing tasks, we need to examine two images or two portions of images on a pixel-by-pixel basis. Jain and Jain developed a 2-D logarithmic searching procedure. Based on a 1-D logarithm search procedure, the 2-D procedure successively reduces the search area, thus reducing the computational burden.