New image processing tools for structural dynamic monitoring

This paper presents an introduction to structural damage assessment using image processing on real data (non ideal conditions). Our contribution is much more a groundwork than a classical experimental validation. After measuring the bridge dynamic parameter on a small resolution video, we conjointly present advantages and limitations of our method. Finally we introduce several "computer vision" based rules and focus on the technical ability to detect damage using camera and video motion estimation

Virtual Prototyping for Dynamically Reconfigurable Architectures using Dynamic Generic Mapping

This paper presents a virtual prototyping methodology for Dynamically Reconfigurable (DR) FPGAs. The methodology is based around a library of VHDL image processing components and allows the rapid prototyping and algorithmic development of low-level image processing systems. For the effective modelling of dynamically reconfigurable designs a new technique named, Dynamic Generic Mapping is introduced. This method allows efficient representation of dynamic reconfiguration without needing any additional components to model the reconfiguration process. This gives the designer more flexibility in modelling dynamic configurations than other methodologies. Models created using this technique can then be simulated and targeted to a specific technology using the same code. This technique is demonstrated through the realisation of modules for a motion tracking system targeted to a DR environment, RIFLE-62

Reconfiguration of Distributed Information Fusion System ? A case study

Information Fusion Systems are now widely used in different fusion contexts, like scientific processing, sensor networks, video and image processing. One of the current trends in this area is to cope with distributed systems. In this context, we have defined and implemented a Dynamic Distributed Information Fusion System runtime model. It allows us to cope with dynamic execution supports while trying to maintain the functionalities of a given Dynamic Distributed Information Fusion System. The paper presents our system, the reconfiguration problems we are faced with and our solutions.Comment: 6 pages - Preprint versio

Dynamic Traffic Signal using Image Processing

In cities, traffic on road is increasing rapidly resulting in traffic jams and reduced traffic flow. Traffic lights play a major role in regulation and management of traffic flow at junctions. These lights are controlled by traffic light controllers (TLCs) that are programmed to assign timely directions to drivers in Red, Yellow and Green signals. Current TLC(s) are based on programmable micro-controllers, which have limitations as their signal timings function according to a program that needs to be modified manually and does not have flexibility to accommodate the functionality to modify signal timings based on variable traffic. In this paper, inspired by advanced technologies, we have studied and tested a method to improve traffic flow at squares run by traffic lights in real-time. To make TLC(s) more efficient, we are proposing a technique which controls green, yellow, red signal switching based on the real-time calculation of traffic density through capturing and processing images of all incoming lanes at any junction. This paper also focuses on the algorithm for scheduling these lights according to vehicle density on the road, thereby aiming at reducing the traffic congestion on squares which will help people reach their destinations safe and in the least time possible

Quantitative modeling of laser speckle imaging

We have analyzed the image formation and dynamic properties in laser speckle imaging (LSI) both experimentally and with Monte-Carlo simulation. We show for the case of a liquid inclusion that the spatial resolution and the signal itself are both significantly affected by scattering from the turbid environment. Multiple scattering leads to blurring of the dynamic inhomogeneity as detected by LSI. The presence of a non-fluctuating component of scattered light results in the significant increase in the measured image contrast and complicates the estimation of the relaxation time. We present a refined processing scheme that allows a correct estimation of the relaxation time from LSI data.Comment: submitted to Optics Letter

A VLSI-oriented and power-efficient approach for dynamic texture recognition applied to smoke detection

The recognition of dynamic textures is fundamental in processing image sequences as they are very common in natural scenes. The computation of the optic flow is the most popular method to detect, segment and analyse dynamic textures. For weak dynamic textures, this method is specially adequate. However, for strong dynamic textures, it implies heavy computational load and therefore an important energy consumption. In this paper, we propose a novel approach intented to be implemented by very low-power integrated vision devices. It is based on a simple and flexible computation at the focal plane implemented by power-efficient hardware. The first stages of the processing are dedicated to remove redundant spatial information in order to obtain a simplified representation of the original scene. This simplified representation can be used by subsequent digital processing stages to finally decide about the presence and evolution of a certain dynamic texture in the scene. As an application of the proposed approach, we present the preliminary results of smoke detection for the development of a forest fire detection system based on a wireless vision sensor network.Junta de Andalucía (CICE) 2006-TIC-235

Design of Novel Algorithm and Architecture for Gaussian Based Color Image Enhancement System for Real Time Applications

This paper presents the development of a new algorithm for Gaussian based color image enhancement system. The algorithm has been designed into architecture suitable for FPGA/ASIC implementation. The color image enhancement is achieved by first convolving an original image with a Gaussian kernel since Gaussian distribution is a point spread function which smoothen the image. Further, logarithm-domain processing and gain/offset corrections are employed in order to enhance and translate pixels into the display range of 0 to 255. The proposed algorithm not only provides better dynamic range compression and color rendition effect but also achieves color constancy in an image. The design exploits high degrees of pipelining and parallel processing to achieve real time performance. The design has been realized by RTL compliant Verilog coding and fits into a single FPGA with a gate count utilization of 321,804. The proposed method is implemented using Xilinx Virtex-II Pro XC2VP40-7FF1148 FPGA device and is capable of processing high resolution color motion pictures of sizes of up to 1600x1200 pixels at the real time video rate of 116 frames per second. This shows that the proposed design would work for not only still images but also for high resolution video sequences.Comment: 15 pages, 15 figure

A Hierarchical Distributed Processing Framework for Big Image Data

Abstract—This paper introduces an effective processing framework nominated ICP (Image Cloud Processing) to powerfully cope with the data explosion in image processing field. While most previous researches focus on optimizing the image processing algorithms to gain higher efficiency, our work dedicates to providing a general framework for those image processing algorithms, which can be implemented in parallel so as to achieve a boost in time efficiency without compromising the results performance along with the increasing image scale. The proposed ICP framework consists of two mechanisms, i.e. SICP (Static ICP) and DICP (Dynamic ICP). Specifically, SICP is aimed at processing the big image data pre-stored in the distributed system, while DICP is proposed for dynamic input. To accomplish SICP, two novel data representations named P-Image and Big-Image are designed to cooperate with MapReduce to achieve more optimized configuration and higher efficiency. DICP is implemented through a parallel processing procedure working with the traditional processing mechanism of the distributed system. Representative results of comprehensive experiments on the challenging ImageNet dataset are selected to validate the capacity of our proposed ICP framework over the traditional state-of-the-art methods, both in time efficiency and quality of results