An overview of SKIPSM (eparated-eme1 jmage £rocessing using Finite state Machines) and some of its applications are presented in a set of companion pers35 This paper describes the application of SKJPSM to certain global image processing operations that are normally considered to be difficult or impossible to perform in a pipelined configuration. These expanded capabilities for pipelined systems are based on the following key theoretical developments: S the separation of certain 2-D image processing operations into a row operation followed by a column operation, S the formulation of these row and column operations in a form compatible with pipelined operation, . the implementation of the resulting operations as simple finite-state machines, and . the automated generation of the finite-state machine configuration data. The operations discussed in this paper are listed below. Many other operations are also possible. S Column,row, and area summation, either over whole images or over sub-regions. . Generation of standard images, such as grey-level wedges with various repeat cycles and directions. S Blob fill and patterned blob fill with arbitrary binary or grey-level texture patterns. . Binarymn-length encoding on the rows or columns of an image. . Multi-levelmn-length encoding on the rows or columns of an image. Speed increases and/or neighborhood size increases by factors of 100 or more can be achieved using conventional pipelined hardware in this new way. Alternatively, inexpensive off-the-shelf "chips" can be configured to carry out the same operations as conventional real-time image processing hardware. Corresponding "speedups" are achieved when the SKJPSM approach is implemented in software.
KEYWORDS: image processing, real time, implementations, finite-state machines, global, run-length encoding