Machine vision is still a challenging topic and attracts researchers to carry out researches in this field. Efforts have been placed to design machine vision systems (MVS) that are inspired by human vision system (HVS). Attention is one of the important properties of HVS, with which the human can focus only on part of the scene at a time; regions with more abrupt features attract human attention more than other regions. This property improves the speed of HVS in recognizing and identifying the contents of a scene. In this paper, we will discuss the human attention and its application in MVS. In addition, a new method of extracting regions of interest and hence interesting objects from the images is presented. The new method utilizes neural networks as classifiers to classify important and unimportant regions.
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