1. A method for generating classifier data structures for classifying graphical objects, the method comprising: receiving, by a processor, an image; detecting, by the processor, a graphical object within the image; defining, by the processor, a bounding region encompassing the graphical object, wherein a border of the bounding region is located a predetermined distance from segments of the graphical object; identifying, by the processor, one or more candidate features of the graphical object within the bounding region, each of the one or more candidate features defined by one or more pixels; comparing, by the processor each of the one or more candidate features to feature definitions defining characteristics of one or more features detectable within one or more graphical objects; determining, by the processor, probabilities that each of the one or more candidate features satisfies a feature definition based on the comparing; and generating, by the processor, a classifier data structure for a graphical object type based, at least in part, on the probabilities.
1. A method for generating classifier data structures for classifying graphical objects, the method comprising: receiving, by a processor, an image; detecting, by the processor, a graphical object within the image; defining, by the processor, a bounding region encompassing the graphical object, wherein a border of the bounding region is located a predetermined distance from segments of the graphical object; identifying, by the processor, one or more candidate features of the graphical object within the bounding region, each of the one or more candidate features defined by one or more pixels; comparing, by the processor each of the one or more candidate features to feature definitions defining characteristics of one or more features detectable within one or more graphical objects; determining, by the processor, probabilities that each of the one or more candidate features satisfies a feature definition based on the comparing; and generating, by the processor, a classifier data structure for a graphical object type based, at least in part, on the probabilities. 3. The method of claim 1 , further comprising determining a graphical object type corresponding to the classifier data structure based on an input received from a user.