Design and Implementation of Parking System Using Feature Extraction and Pattern Recognition Technique

Abstract

With the development of industrial automation, there is a growth in number of vehicles resulted to demand of parking space, which is costly in metropolitan areas. For finding vacant parking facilities, drivers spend more time on roads which causes additional fuel consumption, traffic congestion, and pollution. For addressing parking issues, this study presents a novel framework based on real-time monitoring and image recognition technique. The major contribution of this study is threefold: Initially, analyze the input images which are composed from the event recorders in currently driving cars toward determining the parking spaces availability. Second, this image is preprocessed using a hybrid algorithm, which is a combination of feature extraction (local binary pattern) and pattern recognition (Bayes classifier) technique. With the help of image recognition technique, it can track the availability of parking spaces with images on weather condition. Also, image filtering technique is applied to remove noisy information; hence, we can detect the park lots in any weather condition. Third, consider the utilization of parking facilities, distance to the recommended parking facility, and time to reach from source to destination. Finally, the performance of the suggested technique is validated by the measure of classification accuracy, precision, recall, and f-measure.KeywordsVehicle detectionImage processingSmart parking systemFeature extraction and classification