In this paper a biologically-inspired approach for object search is introduced. This approach is based on the visual information processing in the human brain and more specifically along the two visual processing pathways of the visual cortex. According to this approach different processes, with similar representational structure, work in parallel toward their local tasks, while at the same time, their mutual interaction leads to achievement of larger global goals. The model based on this approach provides a platform where bottom-up and top-down cues are computed and integrated in small incremental steps and lead to emergence of attention that selects an appropriate object. The two important principles of visual information processing, i.e., constraint satisfaction and inhibition play the key role in this model. The model is implemented with an interactive neural network. Simulation results demonstrate the practicality as well as the strength of this approach for object search tasks.