1. A vision system for object recognition, comprising: one or more processors and a memory, the memory having instructions encoded thereon to include: an attention module configured to receive an image representing a scene with an object in the scene and find and extract the object from the image as an extracted object, the attention module also being configured to generate feature vectors corresponding to color, intensity, and orientation information within the extracted object; and an object recognition module configured to receive the extracted object and the feature vectors and associate a label with the extracted object to classify the object, whereby a user can use the vision system to classify an object in a scene; and wherein the attention module is further configured to: receive an image that includes a representation of an object in a scene, the image having color features; determine light and dark intensity channels from the color features; create four fully-saturated color channels from the color features; compute feature opponency maps from the light and dark intensity channels and the four fully-saturated color channels; compute an edge map for each opponency map; segment the scene into a series of “proto-objects” based on the edge maps, where boundaries of the proto-objects are defined by common features between immediate regions within the image; compute a saliency of a given proto-object using color and intensity information contained within the image; rank the proto-objects according to saliency; designate the proto-object with the highest saliency as the object to be extracted from the image; and extract the object from the image.