An FPGA 2D-convolution unit based on the CAPH language

International audienceConvolution is an important operation in image processing applications, such as edge detection, sharpening , adding blurring and so on. Convolving video streams in real-time is a challenging task for PC systems, however, FPGA devices can successfully be used in these tasks. In this article, the design and implementation of a reconfigurable FPGA architecture for 2D-convolution filtering is described. The filtered frames are calculated at a rate of 103 frames per second for images up to 1200×720 pixel resolution. By using a shift-based arithmetic and circular buffers, the developed FPGA architecture allows to reduce the hardware resources consumption up to 98% compared to the conventional convolution implementations , provides high speed processing and enables to manage large number of different convolution kernels. On the other hand, by using the CAPH language it is possible to reduce the design time up to 75% compared to the plain VHDL design. Furthermore, to maintain high flexibility in concordance with the input video, the developed hardware allows to configure the resolution of the input images with values of 3 × Y up to 1200 × Y , and allows scalability for different sizes of convolution kernels of simple and systematic form. Finally , the developed FPGA architecture for the proposed method was implemented and validated in an FPGA Cyclone II EP2C35F672C6 embedded in an Altera development board DE2

Robust sensor fault estimation for descriptor-LPV systems with unmeasurable gain scheduling functions: Application to an anaerobic bioreactor

This paper addresses the design of a state estimation and sensor fault detection, isolation and fault estimation observer for descriptor-linear parameter varying (D-LPV) systems. In contrast to where the scheduling functions depend on some measurable time varying state, the proposed method considers the scheduling function depending on an unmeasurable state vector. In order to isolate, detect and estimate sensor faults, an augmented system is constructed by considering faults to be auxiliary state vectors. An unknown input LPV observer is designed to estimate simultaneously system states and faults. Sufficient conditions to guarantee stability and robustness against the uncertainty provided by the unmeasurable scheduling functions and the influence of disturbances are synthesized via a linear matrix inequality (LMI) formulation by considering H∞ and Lyapunov approaches. The performances of the proposed method are illustrated through the application to an anaerobic bioreactor model

An FPGA stereo matching unit based on fuzzy logic

International audienceThe stereo matching is one of the most widely used algorithms in real-time image processing applications such as positioning systems for mobile robots, three-dimensional building mapping and both recognition, detection and three-dimensional reconstruction of objects. In order to improve the runtime, stereo matching algorithms often have been implemented in dedicated hardware such as FPGA or GPU devices. In this article an FPGA stereo matching unit based on fuzzy logic is described. The proposed method consists of three stages: first, three similarity parameters inherent to each pixel contained in the input stereo pair are determined; later, these parameters are submitted to a fuzzy inference system that determines a value of fuzzy-similarity; finally, the disparity value is determined as the index for the maximum value of the fuzzy-similarity values (zero up to d max). Dense disparity maps are computed at a rate of 76 frames per second for input stereo pairs of 1280x1024 pixel resolution and a maximum expected disparity equal to 15. The developed FPGA architecture provides reduction of the hardware resource demand; up to 67,384, minimum 9,788 for logic units, up to 35,475, minimum 11,766 for bits of memory. Increases the processing speed; up to 78,725,120, minimum 14,417,920 pixels per second and outperforms the accuracy level of most of real-time stereo matching algorithms reported in the literature

Sensor Fault Diagnosis Observer for an Electric Vehicle Modeled as a Takagi-Sugeno System

A sensor fault diagnosis of an electric vehicle (EV) modeled as a Takagi-Sugeno (TS) system is proposed. The proposed TS model considers the nonlinearity of the longitudinal velocity of the vehicle and parametric variation induced by the slope of the road; these considerations allow to obtain a mathematical model that represents the vehicle for a wide range of speeds and different terrain conditions. First, a virtual sensor represented by a TS state observer is developed. Sufficient conditions are given by a set of linear matrix inequalities (LMIs) that guarantee asymptotic convergence of the TS observer. Second, the work is extended to perform fault detection and isolation based on a generalized observer scheme (GOS). Numerical simulations are presented to show the performance and applicability of the proposed method