1. A method for defining a boundary separating a first region and a second region of a digital image, the digital image including one or more color arrangements characteristic of a first visual texture of the first region and one or more color arrangements characteristic of a second visual texture of the second region, the method comprising: selecting, via a user input, a training set of pixels including a portion of the first region and a portion of the second region, the training set of pixels exhibiting sample color arrangements associated with both the first and second visual textures; training a learning machine to classify learning machine input sets based upon the training set, each learning machine input set including a pixel of interest and neighboring pixels; determining using the trained learning machine which pixels of the digital image satisfy criteria for classification as being associated with the first region and second region, by inputting the learning machine input sets each including the respective pixel of interest and the respective neighboring pixels, and outputting an indication of a region to which each of the pixels of interest belong; identifying pixels of the digital image that are determined not to satisfy the criteria for classification as being associated either with the first region or the second region; and decontaminating the identified pixels to define the boundary between the first and second regions by separating pixels of the digital image into pixels associated with the first region, the second region, or the boundary.