Published Paper Details:

Helmet detection method is a combination of classification and cluster. Helmet detection is an important, yet challenging vision task. It is a critical part in many applications such as traffic surveillance. Our proposed method work is as follows, Pre-processing, Feature Extraction and classification. We demonstrate our proposed work by using surveillance traffic videos. Finally, our method will classify whether the person is wearing helmet or not. As far as the robustness and effectiveness are concerned, our method is better than the existing algorithms. The project presents license plate recognition system using connected component analysis and template matching model for accurate identification. Automatic license plate recognition (ALPR) is the extraction of vehicle license plate information from an image. This system model uses already captured images for this recognition process. First the recognition system starts with character identification based on number plate extraction, Splitting characters and template matching. ALPR as a real life application has to quickly and successfully process license plates under different environmental conditions