Massively parallel image processing system for intelligent transportation system applications
09 Nov 1997-pp 367-372
TL;DR: A real-time image processing system for use in intelligent transportation systems that incorporates high-density pixel parallel (HDPP) processor chips into a programmable framework by utilizing the system in a time-sharing fashion.
Abstract: This paper presents a real-time image processing system for use in intelligent transportation systems. The system, run from a desktop computer, incorporates high-density pixel parallel (HDPP) processor chips into a programmable framework. By utilizing the system in a time-sharing fashion, multiple low-level image processing tasks can be implemented on the HDPP hardware. Examples of applications that have been implemented on the system and executed in real time include optical flow, template matching, and stereo vision.
Citations
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27 Jan 2000
TL;DR: Focusing on highway and railway systems, the authors stress the need for computer modeling and simulation to help design and validate complex, large-scale systems and the design of new performance metrics to estimate the performance of these systems.
Abstract: To serve the needs of the future, transportation systems must undergo a radical transformation, from the centralized paradigm to the asynchronous, distributed paradigm that integrates fast computers and high-performance networks through novel computer algorithms. Intelligent Transportation Systems takes the first step towards meeting that challenge. Focusing on highway and railway systems, the authors stress the need for computer modeling and simulation to help design and validate complex, large-scale systems and the design of new performance metrics to estimate the performance of these systems. They present the basic principles related to travel-related decision making, including coordination, control, and routing.
55 citations
Cites background from "Massively parallel image processing..."
...Talib, Love, Gealow, Hall, Masaki, and Sodini [54] propose incorporating a special, high density pixel parallel processor chip onto a desktop computer to achieve fast low-level image processing in ITS systems....
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08 Mar 1999
TL;DR: Modifications to existing techniques commonly used to do real-time image segmentation for efficient hardware implementation of edge detection and edge direction finding techniques may be used within the context of deformable templates for real- time automatic target recognition and tracking.
Abstract: Deconstructing an image based upon it parts poses a challenge to image analysis that may be solved using adaptive algorithms. The presence of occlusion or image rotation makes template matching difficult. Image segmentation techniques can be used to discriminate between objects via feature synthesis using deformable templates. This paper describes modifications to existing techniques commonly used to do real-time image segmentation for efficient hardware implementation. Edge detection and edge direction finding techniques may be used within the context of deformable templates for real-time automatic target recognition and tracking.
3 citations
01 Apr 2016
TL;DR: A new framework with Radio Frequency Identification technology (RFID) applied to road traffic monitoring is exposed and an experiment in a university campus was carried out, concluding the effectiveness of the RFID technology for traffic monitoring.
Abstract: Nowadays the transportation systems show new challenges in management and supervision issues due to amount of vehicles and the variability and extension of the roads. New technologies have been developed to get information about traffic in cities. Nevertheless, new frameworks with different technologies applied to traffic monitoring have not been well defined. In this paper, a new framework with Radio Frequency Identification technology (RFID) applied to road traffic monitoring is exposed. In order to validate the designed framework, an experiment in a university campus was carried out, concluding the effectiveness of the RFID technology for traffic monitoring.
3 citations
Cites methods from "Massively parallel image processing..."
...There are differents techniques to monitor and control traffic based on differents technologies such as image processing [1, 2], magnetic detectors [3], infrared detectors [4], global positioning system (GPS) [5], and Radio Frequency IDentification [6, 7]....
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20 Dec 2008
TL;DR: A multi-DSP real time image processing system based on Rapid IO Protocol is introduced in this paper, its has many characteristics: big data quantity, rapid data transmission, quick data processing and it can carry out large-scale real time signal processing.
Abstract: In recent years, image processing technology has been developed rapidly and presented a relatively obvious development trend. Real time image processing has been widely used. A multi-DSP real time image processing system based on Rapid IO Protocol is introduced in this paper, its has many characteristics: big data quantity, rapid data transmission, quick data processing and it can carry out large-scale real time signal processing.
2 citations
References
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19 Sep 1996
TL;DR: It was recognized that the system was greatly effective for both type of collisions and reduction rates by this safety vehicle for a rear-end collision and a collision encountered at a intersection were estimated.
Abstract: A safety vehicle using an obstacle detection system with a stereo image sensor has been developed. The stereo image sensor was chosen as a more suitable sensor, compared to a laser radar or a millimeter wave radar. The matching method adopted for this stereo system is the small area based matching to yield a distance distribution image. The road shape and solids are recognized from the distance distribution image. This safety vehicle has three functions for the "avoidance stage" proposed in ASV (advanced safety vehicle) project as follows: a collision alarm system; an autonomous collision avoidance system; and a lane-keeping alarm system. Reduction rates by this safety vehicle for a rear-end collision and a collision encountered at a intersection were estimated. It was recognized that the system was greatly effective for both type of collisions.
47 citations
25 Sep 1995
TL;DR: Results obtained are found to be encouraging, indicating that the vision system is useful for developing vision algorithms and that the algorithms based on a part of the proposed ideas are robust for recognition of complex road environment.
Abstract: This paper presents a real-time vision system as a tool of developing robust vision algorithms. Our goal is to develop robust vision algorithms for complex scenes, such as city streets, and for various outside conditions, such as weather, lighting and shading. Since no ordinary computer has enough computational ability for developing vision algorithms efficiently, the system has been developed in the form of compact image processing hardware. We have developed special hardware modules for extracting image features, namely edge segments, depth from stereoscopic and optical flow. A high speed template matching hardware module has been also developed for detecting and tracking objects. Each hardware consists of one or two 6U format VMEbus compatible boards and operates at a video rate due to the pipeline architecture. Experiments have been done on this vision system as follows: road following from edge segments, moving objects detection from optical flow on the images of moving camera, obstacle detection from depth map based on stereoscopic and tracking preceding vehicles by a template matching method. The results obtained are found to be encouraging, indicating that the vision system is useful for developing vision algorithms and that the algorithms based on a part of the proposed ideas are robust for recognition of complex road environment.
46 citations
TL;DR: Three sample applications, smoothing and segmentation, median filtering, and optical flow, establish the suitability of the system for real-time image processing.
Abstract: A system design for performing low-level image processing tasks in real time is presented. The design is based on large processor-per-pixel arrays implemented using integrated circuit technology. Two integrated circuit architectures are summarized: an associative parallel processor and a parallel processor employing DRAM cells. In both architectures, the layout pitch of one-bit-wide logic is matched to the pitch of memory cells to form high-density processing element arrays. The system design features an efficient control path implementation, providing high processing element array utilization without demanding complex controller hardware. Sequences of array instructions are generated by a host computer before processing begins, then stored in a simple controller. Once processing begins, the host computer initiates stored sequences to perform pixel-parallel operations. A programming framework implemented using the C++ programming language supports application development. A prototype system employs associative parallel processor devices, a controller, and the programming framework. Three sample applications, smoothing and segmentation, median filtering, and optical flow, establish the suitability of the system for real-time image processing.
36 citations
19 Sep 1996
TL;DR: The outline of RCAS is described, techniques about the preceding vehicle recognition and collision potential hazard evaluation are described and experimental results about distance headway warning and collision avoidance by automatic braking are reported.
Abstract: RCAS (rear-end collision avoidance system) has been developed as a system of ASV (advanced safety vehicle). It is a driver assist system to avoid the rear-end collision by informing the distance headway. It also has automatic braking function in case of emergency and distance warning function to the trailing vehicle. This paper describes the outline of RCAS, techniques about the preceding vehicle recognition and collision potential hazard evaluation. And experimental results about distance headway warning and collision avoidance by automatic braking are reported.
36 citations
19 Sep 1996
TL;DR: An approach to obstacle detection and steering control for safe car driving is presented based on the evaluation of 3D motion and structure parameters from optical flow through the analysis of image sequences acquired by a TV camera mounted on a vehicle moving along usual city roads, countryroads or motorways.
Abstract: In this work an approach to obstacle detection and steering control for safe car driving is presented. It is based on the evaluation of 3D motion and structure parameters from optical flow through the analysis of image sequences acquired by a TV camera mounted on a vehicle moving along usual city roads, countryroads or motorways. This work founds on the observation that if a camera is appropriately mounted on a vehicle which moves on a planar surface, the problem of motion and structure recovery from optical flow becomes linear and local, and depends on only two parameters: the angular velocity around an axis orthogonal to the planar surface, and the ratio between the viewed depth and the translational speed, i.e. the generalized time-to-collision. Examples of the detection of moving surrounding cars and of the trajectory recovery algorithm on image sequences of traffic scenes from urban roads are provided.
7 citations