1. A feature extracting system for histopathological images comprising: a region segmented image data creating system for histopathological images configured to create region segmented image data required to create a region segmented image in which background regions, cytoplasm regions, and nucleus regions in histopathological image are clearly discriminated; a higher-order local auto-correlation feature computing section configured to compute higher-order local auto-correlation features by scanning a segmented histopathological image created by the region segmented image data creating system using a plurality of predetermined local pattern masks; a component feature vector computing section configured to obtain a weighted sum of the higher-order local auto-correlation features by adding the higher-order local auto-correlation features belonging to the same invariant feature group which consists of a plurality of local pattern masks which can be considered to be equivalent to each other when they are flipped and/or rotated by 45 degrees or multiples of 45 degrees; and a feature extracting section configured to extract the features of the histopathological image based on the weighted sum of the higher-order local auto-correlation features, wherein: the region segmented image data creating system for histopathological images includes: a first bi-level image data creating section operable to create first bi-level image data, in which the nucleus regions can be discriminated from the other regions, from the histopathological image data; a second bi-level image data creating section operable to create second bi-level image data, in which the background regions can be discriminated from the other regions, from the histopathological image data; and a three-level image data creating section operable to create three-level image data as the region segmented image data by computing a negative logical addition of the first bi-level image data and the second bi-level image data in order to clarify cytoplasm regions.