Cognitive Informatics based DIND for Corner and Crossing Detection in Intelligent Space

Intelligent space is a space of distributed sensory intelligence and actuators. The basic component of intelligent space is the distributed intelligent network device (DIND), responsible for intelligent sensing and estimation. It is important for intelligent space to be aware of state of its internal environment, such as the class and position of objects it contains. The ability of object recognition is thus necessary in intelligent space. Existing cognitive computational systems like the mammalian cortex perform extremely well when it comes to visual object recognition. Psychological experiments have shown that image features such as edges and especially corners are of great importance in cognitive object recognition. Inspired by cognitive recognition systems, the proposed cognitive informatics model addresses the problem of vertex and corner detection. The model integrates the previously developed visual feature array (VFA), which is a cognitive model of oriented edge detection. The ultimate goal of the presented model is to provide suitable input for a cognitive object recognition system