AN OPTIMIZATION APPROACH TO AUTOMATIC SENSOR AND LIGHT SOURCE POSITIONING FOR A MACHINE VISION TASK, WHERE GEOMETRIC MEASUREMENT AND/OR OBJECT VERIFICATION IS IMPORTANT, IS DISCUSSED. THE OPTIMAL SENSOR AND LIGHT SOURCE POSITIONS ARE DEFINED IN SUCH A WAY THAT WHEN THE SENSOR AND LIGHT SOURCE ARE PLACED IN THE OPTIMAL POSITIONS, A PICTURE PRODUCES THE MINIMUM VARIANCE FOR THE REQUIRED MEASUREMENT. AN OPTIMIZATION PROCEDURE EMPLOYING MATHEMATICAL PROGRAMMING TECHNIQUES USES EDGE CONTROL TO DETERMINE THE BEST POSITIONS FOR THE LIGHT SOURCE AND SENSOR TO PERFORM THE REQUIRED MEASUREMENT. A SERIES OF EXPERIMENTS WAS CONDUCTED TO DEMONSTRATE THE FEASIBILITY OF OUR OPTIMIZATION APPROACH. THE OPTIMAL POSITIONS COMPUTED BY THE PROGRAM WERE FOUND TO BE THE BEST ONES IN THE REAL EXPERIMENTS. FURTHERMORE, THE CORRELATION COEFFICIENT BETWEEN THE EXPECTED VARIANCE AND THE VARIANCE COMPUTED FROM THE