Algorithmic Specified Complexity Part III: Measuring Meaning in Images

In this, the third and final podcast of the series, Dr. Winston Ewert explains the role of context in measuring meaning in images. A non-humanoid gelatinous alien would assign no meaning to the faces on Mount Rushmore if the alien had never before seen a humanoid. Humans, on the other hand, have the context of familiarity with human heads and historical figures that allow them to assxign high algorithmic specified complexity when viewing Mount Rushmore. Information theoretic-based algorithmic specified complexity applied to images is developed in the peer-reviewed archival journal article:

Winston Ewert, William A. Dembski, Robert J. Marks II. "Measuring meaningful information in images: algorithmic specified complexity," IET Computer Vision, 2015, Vol. 9, #6, pp. 884–894 DOI: 10.1109/TSMC.2014.2331917

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