Deep Neural Networks are built to generalize outside of training set in mind by using techniques such as regularization, early stopping and dropout. But considerations to make them more resilient to adversarial examples are rarely taken. As deep neural networks become more prevalent in mission critical and real time systems, miscreants start to attack them by intentionally making deep neural ne...

This paper presents an automatic road sign recognition system. The system bases on twodimensional hidden Markov models. First, a study of the existing road sign recognition research is presented. In this study, the issues associated with automatic road sign recognition are described, the existing methods developed to tackle the road sign recognition problem are reviewed, and a comparison of the...

This paper describes a method for detecting and recognizing road signs in grey-level and colour images acquired by a single camera mounted on a moving vehicle. The method works in three stages. First, the search for the road sign is reduced to a suitable region of the image by using some a priori knowledge on the scene or colour clues (when available). Secondly, a geometrical analysis of the ed...

We present a real-time approach for circular and polygonal road signs detection in still images, regardless of their pose and orientation. Object detection is done using a pairwise gradient-based symmetry transform able to detect circles and polygons indistinctly. This symmetry transform of gradient orientation, the so-called Bilateral Chinese Transform BCT, decomposes an object into a set of p...

We briefly review the advances in driver assistance systems and present a realtime version that integrates single view detection with region-based 3D tracking of traffic signs. The system has a typical pipeline: detection and recognition of traffic signs in independent frames, followed by tracking for temporal integration. The detection process finds an optimal set of candidates and is accelera...

ABSTARCT: Most of the Indian rural and suburban roads are not ideal for driving due to improper and invisible road signs. This has led to many accidents causing loss of lives and severe damage to vehicles. Many techniques have been proposed in the past to detect these problems using image processing methods. But there has been little work specifically carried out for detecting the issue of road...

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 f...

This paper presents a framework for incremental detection of text from road signs. The approach efficiently incorporates tracking and detection mechanisms into the same framework. The proposed approach first finds a set of discriminative feature points and clusters them into different regions. We then select candidate sign planes by a combination of color and vertical plane models. Within detec...

STEREOSCOPIC VISION IN VEHICLE NAVIGATION Behnoush Abdollahi August 5, 2011 Traffic sign (TS) detection and tracking is one of the main tasks of an autonomous vehicle which is addressed in the field of computer vision. An autonomous vehicle must have vision based recognition of the road to follow the rules like every other vehicle on the road. Besides, TS detection and tracking can be used to g...

Road Sign Detection is a major goal of the Advanced Driving Assistance Systems. Most published work on this problem share the same approach by which signs are first detected and then classified in video sequences, even if different techniques are used. While detection is usually performed using classical computer vision techniques based on color and/or shape matching, most often classification ...