Multi Traffic Scene Perception Using Support Vector Machine and Digital Image Processing

Traffic accidents are especially intense for a rainy day, Night, rainy season, rainy season, ice and day without street lighting many low-level conditions. Current View Drive the help systems are designed to be done under good-nature Weather. Classification is a method of identifying Optical characteristics of vision expansion protocols more efficient. Improve computer vision in awkward manner Weather environments, multi-class weather classification system many weather features and supervision were made Learning. First, basic visual features are extracted Multiple traffic pictures, then the feature is revealed. The team has eight dimensions. Secondly, five supervision was made Learning methods are used to train instructors. Analysis the extracted features indicate that the image describes accurately the highest recognition of etymology and classmates is the accuracy rate and adaptive skills. Provides the basis for the proposed method anterior vehicle innovation increases invention Night light changes, as well as increases View of driving field on an ice day. Image feature extraction is the most important process in pattern recognition and it is the most efficient way to simplify high-dimensional image data. Because it is hard to obtain some information from the M × N × 3-dimensional image matrix. Therefore, owing to perceive multi-traffic scene, the key information must be extracted from the image