Depth estimation from image defocus using fuzzy logic

A method for improving the accuracy of depth-from-defocus is presented. Fuzzy logic is combined with a depth-from-defocus technique to correct for uncertainty and imprecision in depth estimation. Two inputs to the fuzzy algorithm are the focus quality and the focal error. Focus quality is a measure of the amount of defocus in an image. Focal error is the difference in focus between corresponding points in images with different apertures. The output is the depth estimation for objects in images that may be either blurred or in focus. Experiments show that fuzzy logic significantly improves depth estimation compared to the nonfuzzy depth-from-defocus method. The estimation error using fuzzy logic is less than 1.5% over an object distance from 7 to 11 feet. Therefore, this method improves the accuracy of the depth-from-defocus method, while maintaining simplicity. This method was implemented using a standard camera lens and an ANDROX imaging board