Moving Objects Detection Using Intersecting Cortical Model in Enhanced Fish-eye Image

A new method of the moving objects detection using the enhanced fish-eye lens and the intersecting cortical model(ICM) algorithm is proposed. The improved fish-eye lens is designed through controlling the entrance pupils of the lens. This lens has an ultra field of view about 183 degrees,and can image an ellipse picture on the 4∶3 rectangular CCD surface,which increases the CCD utilization and the image resolution. The ICM is a model based on pulse coupled neural network(PCNN) which is especially designed for image processing. It is derived from several visual cortex models and is basically the intersection of these models. The theoretical foundation of the ICM is given. An improved ICM algorithm in which some parameters are modified is used to detect moving objects specially. The experiment indicated that moving objects can be detected reliably and efficiently using ICM algorithm from the elliptical fish-eye image. It can be used in the field of traffic monitoring and other security domains.