Job-shop scheduling applied to computer vision

This paper presents a method for minimizing the total elapsed time spent by n tasks running on m differents processors working in parallel. The developed algorithm not only minimizes the total elapsed time but also reduces the idle time and waiting time of in-process tasks. This condition is very important in some applications of computer vision in which the time to finish the total process is particularly critical-quality control in industrial inspection, real-time computer vision, guided robots,.... The scheduling algorithm is based on the use of two matrices, obtained from the precedence relationships between tasks, and the data obtained from the two matrixes. The developed scheduling algorithm has been tested in one application of quality control using computer vision. The results obtained have been satisfactory in the application of different image processing algorithms