Finite state automata and image recognition

#Finite state automata and image recognition series#

Every component of the image size measurement system is indispensable, and the measurement algorithm is the most important. The hardware such as camera and image processing algorithm make up the image size measurement system and finish the measurement work on this platform. The object of interest is segmented from the background by image segmentation, and the parameters such as dimension are important for feature extraction and parameter measurement. Image preprocessing can suppress noise and enhance contrast, thus improving the quality of source image. The focus of image acquisition is to obtain high-quality image. Image size measurement includes image acquisition, image preprocessing, image segmentation, feature extraction, and parameter measurement. The difference in reaction time of the manually driven vehicle system reduces the reaction time of the automatic driving system, so that the road capacity is greatly improved. In the autopilot study, by establishing a single-lane autopilot-manual driving traffic flow model, the unit length of the cell is refined, and autopilot is fully considered. The simulation results can provide the preparation of contingency plans, staff training, the evacuation of passengers, and emergency drills with a reference.ДЄnother major research area of cellular automata is autopilot. And the analysis and assessment of the traffic situation has high application value in airport surface.ДЄiming at the actual situation of complex structure and the evacuation of subways affected by the subjective conditions of pedestrians, these papers use the ant colony algorithm to solve the large passenger flow under complex building structure to find the optimal evacuation path in the macro view, and on the micro-level, use the intelligent decision model of cellular automaton to construct the underground pedestrian evacuation model of the fusion of ant colony algorithm and cellular automaton and discuss the evacuation efficiency and individual status of a station in Guangzhou Metro during the evacuation of pedestrians. Simulation results show that the simulation method has the characteristics of simple, high efficiency, and high accuracy, which can reflect the autonomy and individual differences of aircraft taxi in airport traffic system. The airport surface traffic is simulated. Different parts of the airport surface traffic are defined respectively as one-dimensional cellular automaton, and aircraft agent is designed, which means that a traffic simulation model is constructed based on agent-cellular automaton. The combination of agent theory and the cellular automaton model is discussed. The traffic characteristics of airport surface are analyzed. proposed an airport surface traffic simulation method based on the theory of agent and cellular automaton model. In order to analyze the traffic situation of airport surface, Xing et al. In addition, grille space can be limited or infinite. The grid space can be one-dimensional, two-dimensional, or high-dimensional.

#Finite state automata and image recognition series#

The space of cellular automata is composed of a series of cells arranged in grid distribution. Therefore, cellular automata have become an extreme representative in the field of discrete dynamical systems. The values of space and state variables are continuous. If mapping corresponds to ordinary differential equations in continuous dynamical systems, then cellular automata correspond to partial differential equations in continuous dynamical systems, because partial differential equations are in time. The mapping is similar to cellular automata in some aspects, the mapping is discrete in time evolution, and the value of state variables of cellular automata is continuous. Cellular automata are a discrete dynamic system in space, time, and state.