1,721,113 research outputs found
Image Processing for Vehicular Applications
No full textIn developing a vision system for a vehicle, different setup constraints and issues must be considered.
Space, wiring, or lighting are also typical issues to be also faced in industrial scenarios; nevertheless, when a vision system has to be deployed inside a vehicle they have to be more carefully studied and often drive the hardware selection.
Moreover, cameras are to be installed on moving vehicles and this led to additional problems to be faced. In fact, camera movements, oscillations and vibrations, or different and even extreme illumination conditions have to be taken in account when developing machine vision software
Tools for code optimization and system evaluation of the image processing system PAPRICA-3
No full textThis paper presents the complex environment that was built to ease the prototyping of real-time applications on the PAPRICA-3 massively parallel system. Applications are developed in C++ using high level data types and the corresponding Assembly code is automatically created by a code generator. A stochastic code optimizer takes the assembly code and improves it according to a genetic approach; due to the high computational power required by this approach, the stochastic code optimizer was implemented with MPI and runs in parallel on a cluster of workstations. The availability of this complex environment allowed to test the performance of the system and to tune it according to some target applications before the actual development of the hardware. For this purpose a system-level simulator was also built to determine the number of clock cycles required to run a specific segment of code. The whole environment has been used to validate possible solutions for the hardware system and to develop, test, and tune several real-time image processing applications. The hardware system is now completely defined
GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection
No full textThis paper describes the generic obstacle and lane detection system (GOLD), a stereo vision-based hardware and software architecture to be used on moving vehicles to increment road safety. Based on a full-custom massively parallel hardware, it allows to detect both generic obstacles (without constraints on symmetry or shape) and the lane position in a structured environment (with painted lane markings) at a rate of 10 Hz. Thanks to a geometrical transform supported by a specific hardware module, the perspective effect is removed from both left and right stereo images; the left is used to detect lane markings with a series of morphological filters, while both remapped stereo images are used for the detection of free-space in front of the vehicle. The output of the processing is displayed on both an on-board monitor and a control-panel to give visual feedbacks to the driver. The system was tested on the mobile laboratory (MOB-LAB) experimental land vehicle, which was driven for more than 3000 km along extra-urban roads and freeways at speeds up to 80 km/h, and demonstrated its robustness with respect to shadows and changing illumination conditions, different road textures, and vehicle movemen
Vision-based vehicle guidance
No full textThis implementation of lane and obstacle detection for an autonomous, self-guided vehicle succeeds by tailoring vision and computational techniques to an affordable SIMD architecture. The authors use a geometrical transform called inverse perspective mapping (IPM). Using a priori knowledge of both the scene and the acquisition device, the IPM technique allows one to remove the perspective effect and produce a new image in which the information content is homogeneously distributed among all pixels. In the remapped image, the amount of information carried by each pixel no longer depends on the pixel's position, making the SIMD approach practica
Development and Test of an Intelligent Vehicle Prototype
No full textThis paper presents the current status of the ARGO Project, whose main target is the development of an active safety system and an automatic pilot for a standard road vehicle. First the ARGO project is briefly described along with its main objectives and goals; then the autonomous vehicle prototype and its functionalities are presented. An overview of the computer vision algorithms for the detection of lane markings, generic obstacles, leading vehicles and pedestrians is given
Individuazione dei Bordi Strada e della Corsia di Marcia mediante Computazione Massivamente Parallela
No full textThis paper describes an approach to real-time road/lane detection from image sequences acquired from a vehicle running on extra urban roads. The distinguishing characteristic of the approach is that the algorithm is suited for implementation on PAPRICA massively parallel architecture. The real time road/lane detecion system has been tested on the MOB-LAB experimental vehicle
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