An Iterative Morphological Fuzzy Rule Based Classifier For Moving Vehicle Recognition - et. al., I. Jothipriya , (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
A novel fuzzy rule based classifier to detect and recognize the type of moving vehicle from video frame using iterative morphological image processing operations is presented in this research work. A traffic video for a time period is captured, converted into still frames, pre-processed by iterative morphological filter, foreground objects are extracted by Background Subtractiontechnique,boundaries of the vehicles are extracted by morphological operation and the detected vehicles are isolated by Bounding Box method. Fuzzy Rule based classifier is constructed to categorize and recognize the vehicles into different types(Car, Bike, Bus, Container& Truck) based on the structural features Height, Width and Area of the bounding boxes. Finally the proposed method is evaluated with the classification metrics confusion matrix, precision and accuracy and the experimental results show that the performance of the proposed system goes beyond that of the existing video-based vehicle classification techniques yielding 84% of accuracy.