Traffic and railroad signs detection in images and in point cloud – overview of existing algorithms

Agnieszka Moskal
AGH University of Science and Technology
Faculty of Mining Surveying and Environmental Engineering
Poland

Elżbieta Pastucha
AGH University of Science and Technology
Faculty of Mining Surveying and Environmental Engineering
Poland

Abstract

During the last fifteen years, automatic sign recognition in different type of data has become the subject of many studies. Reasons for these works fall into one of two categories: inventory purposes or drivers assistance systems. Depending on the purpose of the systems, various types of sensors, acquiring different type of data, are implemented. Due to their application, drivers assistance systems need small sensors, bringing limited amount of data, while systems for inventory purposes can use complex measuring systems, integrating different types of sensors and providing high accuracy and large volume data. The time is also at issue. Detection and classification of a sign in driver assistance systems has to be done in real time, while processing of data for inventory purposes can be done off–line. Also global positioning of identified signs is significant only in the latter systems. Structures of proposed algorithms vary and use many different concepts, both from math and information processing. In this paper, basic concepts of most important algorithms from the last fifteen years are presented. Data acquisition process and measuring systems are described shortly. Then, data pre-processing, concepts of detection and, finally, concepts of classification are broadly covered.

Keywords:

traffic signs; railroad signs; template recognition; sign detection; sign classification

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