1. A computer based partitioned modeling method for flexible recognition and extraction of patterns directed by human comprising the steps of: a) Input a plurality of user directed specification of image regions from learning image to be processed including “Patterns to enhance” region, “Patterns to suppress” region and “Background” region; b) Perform feature extraction on the image region having characterization feature output wherein the characterization feature output contains features derived from pre-processed grayscale intensity statistics of the image to be processed; c) Perform a plurality of hierarchical clustering using the characterization feature for background pattern removal and remaining patterns for patterns to enhance and patterns to suppress having a plurality of hierarchical partitions outputs corresponding to background, patterns to enhance and patterns to suppress; d) Perform model generation using the hierarchical partitions for each of the background, patterns to enhance, and patterns to suppress having their partition model outputs wherein the model generation further comprises a background learning step, a foreground pattern extraction step and a foreground pattern learning step and wherein the partition model outputs are used for partitioned matching for recognition and extraction of patterns.