a precursor to the kriged estimate or kriged estimator. In mathematical statistics, Matheron’s k* is the length-weighted average grade of a single panneau in his set. What Matheron failed to derive in this paper was var(k*), the variance of his estimateur. Matheron presented his Stationary Random Function at the first colloquium on geostatistics in the USA. He called on Brownian motion to conjecture the continuity of his Riemann integral but did not explain what Brownian motion and ore deposits have in common. Matheron, unlike John von Neumann in 1941 and Anders Hald in 1952, never worked with Riemann sums. It was not Professor Dr Georges Matheron but Dr Frederik P Agterberg who derived the distance-weighted average of a set of measured values determined in samples selected at positions with different coordinates in a sample space. What Agterberg did not do was derive the variance of this function. Matheron did indeed derive length-weighted average grades of core samples and ore blocks but did not derive the variance of these functions. In time, the length-weighted average grade for Matheron's three-dimensional block grade was replaced with the distance-weighted average grade for Agterberg's zero-dimensional point. Both central values turned into honorific kriged estimates or kriged estimators. An infinite set of Agterberg's zero dimensional points fits within any ore block, along any borehole, or inside any sampling unit or sample space. Matheron's block grades and Agterberg's point grades are unique because both are functions without variances. Mathematical morphology In 1964, Matheron was supervising the PhD thesis of Jean Serra, dedicated to quantifying the ore properties of the iron deposit of Lorraine. Serra came up with the idea of using structuring elements for the analysis, which led to the concept of hit-or-miss transform. The theoretical analysis of this transform led Matheron to derive and investigate the concepts of erosion, dilation, opening and closing, which became known later as the basic morphological operators. He also developed a tool for granulometry, i.e., the computation of a "size distribution", where he mathematically characterizes the concept of size. In December 1964, Matheron and Serra, together with Philippe Formery, named this approach mathematical morphology. It has since evolved into a theory and method that is applied in a variety of image processing problems and tasks, and is researched worldwide (main article: Mathematical morphology). Matheron continued to contribute to mathematical morphology during the years, his best-known contribution being the morphological filtering theory,