جستجوی مقالات مرتبط با کلیدواژه « object detection from video » در نشریات گروه « مکانیک »

Design of a new intelligent driver assistance system based on traffic sign detection with Persian context is concerned in this paper. The primary aim of this system is to increase the precision of drivers in choosing their path with regard to traffic signs. To achieve this goal, a new framework that implements fuzzy logic was used to detect traffic signs in videos captured along a highway from a vehicle. Implementing fuzzy logic in smart systems increases its inference and intelligent capabilities that results in better decision making in real-time conditions. In order to detect road sign’s texts, the combination of Canny Edge Detector Algorithms and Maximally Stable Extremal Regions (MSER) is used. Regions of an image that vary in properties, such as color or brightness, with respect to surrounding regions, are detected with the help of MSER algorithm. By using a multi-stage algorithm, Canny edge detector detects a wide range of edges in the acquired images. In order to join the individual characters for the final stage of detection of texts in traffic signs, a morphological mask operator is used. Finally, the recognition of the detected texts is carried out by employing MATLAB Optical Character Recognition (OCR). The overall accuracy of this new framework in detecting and recognizing texts is 90.6%.

In recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. Detection of traffic signs is an effective method to reach the mentioned aims. In this paper a new intelligent driver assistance system based on traffic sign detection with Persian context is designed. The main goal of this system is to assist drivers to choose their path based on traffic signs more precisely. To reach this purpose, a new framework by using of fuzzy logic was used for detection of traffic signs in videos which have has been captured from a vehicle path in highways. Fuzzy logic increases inference and intelligent capabilities in smart systems to make correct decision making in online conditions. Then, the combination of Maximally Stable Extermal Regions (MSER) and Canny Edge Detector Algorithms are used to detect road sign’s texts detection. MSER algorithm is aimed at assists to detect regions in an image that differ in properties, for example in brightness or color, compared to surrounding regions. Also, canny edge detector uses a multi-stage algorithm to detect a wide range of edges in the images. Thereafter, morphological mask operator is used to join individual characters for final detection of texts in the traffic signs. Finally, MATLAB Optical Character Recognition (OCR) is employed to recognize the detected texts. This new framework gives an overall text detection and recognition rate of .