Traffic sign shape classification based on correlation techniques
نویسندگان
چکیده
In this paper we present a correlation-based matching method for traffic sign shape classification. Our purpose is to offer a robust and reliable framework which can be used in numerous applications like driver assistance systems. The shape classification is scale, translation and rotation invariant. The process involves obtaining essential features (e.g. edges, ridges, corners) from each area, and comparing it to the stored templates of known patterns. The algorithm is very flexible, easy to reconfigure for many different shapes and the results we obtained show the success rate. Key-Words: Advance driver-assistance systems (ADASs), intelligent vehicles, road sign detection and classification.
منابع مشابه
Classification of encrypted traffic for applications based on statistical features
Traffic classification plays an important role in many aspects of network management such as identifying type of the transferred data, detection of malware applications, applying policies to restrict network accesses and so on. Basic methods in this field were using some obvious traffic features like port number and protocol type to classify the traffic type. However, recent changes in applicat...
متن کاملTraffic Sign Recognition-based Vehicle Speed Regulation
This paper purposed a Traffic Sign Recognition (TSR) system which can automatically detect and classified the traffic signs in traffic scene images acquired from a moving car. First it uses color based segmentation and then further refines the segments using two shape detection based techniques. A color description technique is used to extract the sign information from the segmented part which ...
متن کاملResearch on Traffic Sign Classification Algorithm Based on SVM
A coarse-to-fine traffic sign classification algorithm is proposed. The task for traffic sign classification is to analyze the detected regions and determine the class of the sign in the region. By analyzing existing traffic sign classification algorithms, the major problem affecting the classification accuracy is pointed out. Based on this analysis, a coarse-tofine classification algorithm is ...
متن کاملAnalysis of Speed Sign Classification Algorithms Using Shape Based Segmentation of Binary Images
Traffic Sign Recognition is a widely studied problem and its dynamic nature calls for the application of a broad range of preprocessing, segmentation, and recognition techniques but few databases are available for evaluation. We have produced a database consisting of 1,300 images captured by a video camera. On this database we have conducted a systematic experimental study. We used four differe...
متن کاملA novel pLSA based Traffic Signs Classification System
In this work we developed a novel and fast traffic sign recognition system, a very important part for advanced driver assistance system and for autonomous driving. Traffic signs play a very vital role in safe driving and avoiding accident. We have used image processing and topic discovery model pLSA to tackle this challenging multiclass classification problem. Our algorithm is consist of two pa...
متن کامل