The obstacle detection field is a very broad one and a lot of obstacle detection systems have been developed in the last years in this domain. We tried to identify the main character of an obstacle detection system from the ruttier scene. Thus, we classified the main types of sensors from this field in passive (visible and infrared spectrum camera) and active (radar, laser-scanner, sonar) sensors and we made a survey in this domain. After a short presentation of every type of sensor, we presented another current andfancy solution for an obstacle detection system. the fusion of different sensor together. Almost all obstacle detection systems use a combination ofpassive-active technology, and in general the best solution is obtained using a vision system combined with a distance sensor like radar or laser. Maybe the most low-priced system is one combining only vision systems, but the inconvenient in this case is the lack ofdistance information.
We develop an algorithm that automatically finds and extracts the iris information in an image containing a human eye.The purpose of this paper is to identify the colored information contained in the iris circular zone and to remove the insignificant information about pupil and external zone of the iris.We focus on image analysis and image enhancement by image filtering, edge detection and morphological operations like dilation and filling. Using a personal approach that automatically detects the center of a region, we find the center of the iris, respectively the center of the pupil.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.