Complex environment perception and positioning based visual information retrieval

Abstract

The biological vision model is devoted to provide a novel technology approach by merging new cognitive visual features with inspired nerve cells cognitive intelligence cortex and try to relate with real worlds object recognition. To perceive an arbitrary natural scene from complex environment perception and sensing in robotic mobility and manipulation on unstructured random natural scene understanding is a challenging problem in the visual image processing. This paper has considered neural network (NN) which is nothing but the grid of “neurons like” nodes. Based on the NN technique,the authors have proposed a new scheme for the scene understanding and recognition. In addition, the significant intellectual visual features are also incorporated for scene expression; those are very crucial and provide cognitive intelligence to robot vision. Due to the dynamic nature of artificial neural network intelligence, we have adapted the attributes of the Gabor filter and Laplacian of Gaussian filter; those play the significant role in the robot visual perception. Through the study of perceptual ability of the natural scene image from complex environment for robot vision is enhanced with the integration of cognitive visual features and the scene expression.