The real-time performance of a universal thresholding algorithm for machine vision with nonstructured light

The extraction of useful image data is achieved by a nonlinear thresholding technique which has been shown to yield useful practical results in a number of different applications through an ad-hoc experimental approach to the establishment of the appropriate thresholding algorithm. The paper illustrates the systematic establishment of the nonlinear algorithm and the resulting real-time performance of the optimal threshold function for an input image with a simple sample object. The use of the method for inspection applications is discussed briefly