| 摘要 |
PURPOSE:To stably perform local binarization without increasing the volume of processing calculation by classifying the property of each local area based on primary moment feature (statistic) quantity and adaptively determining a binarizing threshold while taking properties of nearly local are and the primary moment feature quantity into consideration. CONSTITUTION:The feature quantity of 3X3 nearby local areas A-I is used for the purpose of determining the binarizing threshold of a local area E, and each local area (i) is classified in accordance with unimodality (s) or bimodality (b). Local areas A, D, G, and H having bimodality (b) are selected, and the binarizing threshold is determined in accordance with an average density value and the number of picture elements of four object classes and those of four background classes. That is, a back-ground class average density value -mu0(b) of four local area having bimodality (b) and an object class average density value -mu1(b) of four local areas are calculated, and a binarizing threshold SL is determined by these averages. Thus, only circuits for product sum calculation are used even if the density of the object in a picture is not uniform, and the volume of processing is reduced and the binarizing threshold is stably determined.
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