1. An automated visual processing system comprising: a memory; an information processor and controller, communicatively coupled with the memory; a video imaging system, communicatively coupled with the information processor and controller and the memory, for receiving a plurality of images representing frames of a video sequence of an external environment of a vehicle; a blob detector, communicatively coupled with the video imaging system, the information processor and controller, and the memory, for identifying a blob within each frame of the plurality of images; a blob feature extractor, communicatively coupled with the blob detector, for extracting a plurality of features from a blob found by the blob detector; a blob classifier, communicatively coupled with the blob feature extractor and the blob detector, for recognition of a type of a blob, selected from a plurality of types of blobs, that is found by the blob detector, wherein the blob classifier is a machine learning classifier that utilizes a support vector machine model to recognize the plurality of types of blobs, wherein the support vector machine model has been trained with respect to the plurality of types of blobs; and an event controller, communicatively coupled with the blob classifier and the blob detector, for determining a binary decision based at least on the recognized type of blob that is found by the blob classifier and a set of rules comprising at least one rule for detecting a given environment type based on calculated ambient brightness and average edge energy of frames of the plurality of images, and performing an action based on such decision.