基于MAX5307和DSP的多回路测控系统设计

提出了一种多回路测控系统的设计方案。该方案仅使用一个DSP(数字信号处理器)及一个多通道集成的D/A转换器件MAX5307,不仅同时保证了多个测控回路的实时性及控制精度,而且实现简单,成本低廉。文中结合实际系统,给出了其具体的硬件和软件实现。该方法具有广泛的适用性,对类似系统的设计具有参考价值。

微型ROV控制装置及控制方法

介绍了一种基于嵌入式ARM9技术的微型ROV的控制装置及控制方法。该装置可以同时进行两通道串行通讯,实现微型ROV的视频信号、潜水深度、艏向角度、纵倾角度、横摇角度、电子舱温度等数据的采集和与上位机的通讯传输;该装置可以采集16路模拟量信号和12路数字量信号,输出4路模拟量信号和12路TTL电平信号,实现推进器、水下灯、水下摄像机、云台等ROV功能器件的驱动。该装置具有通讯能力强、集成度高、功耗低等特点,可以满足微型ROV所有的常用功能要求。

多路温度测控系统的设计

目的利用单片机技术设计多路温度测控系统,实现多路温度的测量和控制.方法系统以单片机AT89C52为核心,利用多路转换器和新型数字器件MAX6675构成8路K型热电偶温度测量电路,利用D/A转换器AD7528和驱动电路构成输出电路,实现8路一一对应的闭环温度测量控制.系统软件采用PID控制器.结果实践证明,可根据需要增减系统温度信号采样通道的数目,使用软件抗干扰措施,提高了采样数据的可靠性.简化了输入输出硬件结构,使系统具有低成本高速度和较好的测量控制精度.结论多路温度测控系统作为整机适用于现场测量控制应用,也可作为多路温度控制模块应用在体积小、温度测量精度要求较高的大型系统中.

宽频带地震数据采集系统的研制

The seismic data acquisition system is the most important equipment for seismic prospecting. The geophysicists have been paying high attention to the specification of the equipment used in seismic prospecting. Its specification and performance are of great concerned to acquire precisely and accurately seismic data, which show us stratum frame. But, by this time, limited by the technology, most of the Broad-band Seismic Recorder (BSR) for lithosphere research of our country were bought from fremdness which were very costliness and maintained discommodiously. So it is very important to study the seismic data acquisition system.The subject of the thesis is the research of the BSR, several items were included, such as: seismic data digitizer and its condition monitor design.In the first chapter, the author explained the significance of the implement of BSR, expatiated the requirement to the device and introduced the actuality of the BSR in our country.In the second chapter, the collectivity architecture of the BSR system was illustrated. Whereafter, the collectivity target and guideline of the performance of the system design were introduced. The difficulty of the system design and some key technology were analyzed, such as the Electro Magnetic Compatibility (EMC), system reliability technology and so on.In the third chapter, some design details of BSR were introduced. In the recorder, the former analog to digital converter (ADC) was separated from the later data transition module. According to the characteristic of seismic data acquisition system, a set high-resolution 24-bit ADC chip was chosen to the recorder design scheme. As the following part, the noise performance of the seismic data channel was analyzed.In the fourth chapter, the embedded software design of each board and the software design of the workstation were introduced. At the same time the communication protocol of the each module was recommendedAt the last part of this thesis, the advantages and the practicability of the BSR system design were summarized, and the next development items were suggested.

Mapeamento de uso das terras utilizando processamento digital de imagem de sensoriamento remoto.

O uso dos métodos tradicionais de levantamento do uso das terras, em razão do custo elevado dos instrumentos e a dificuldade de disponibilizar as informações de maneira rápida aos tomadores de decisão, torna proibitivo seu emprego de forma sistemática e repetitiva sobre grandes extensões de território. Desta forma, existe a necessidade de se utilizar métodos que possibilitem o levantamento do uso das terras de maneira eficiente, rápida e que tenham relativamente baixo custo. Neste contexto, a forma mais eficiente e rápida para caracterizar o uso atual das terras é por meio dos recursos instrumentais oferecidos pelo sensoriamento remoto (SR), com auxílio dos Sistemas de Informações Geográficas (SIGs) e dos Sistema de Posicionamento Global (GPSs). O processo de levantamento e caracterização do uso das terras, nesse caso, pode ser grandemente facilitado pela utilização de imagens de satélites e outros recursos de sensoriamento remoto, que podem gerar dados passíveis de serem geocodificados, ou seja, integrados, relacionados e espacializados nos SIGs. Esses, em conjunto com os GPSs, são considerados, atualmente, como a maneira mais eficiente de levantamento e identificação do uso das terras. Desta forma, o trabalho teve como objetivo o mapeamento de uso das terras utilizando o processamento digital de imagem de sensoriamento remoto, utilizando-se a interpretação visual, a classificação digital supervisionada, e a classificação híbrida (classificação digital + interpretação visual), utilizando-se imagem TM do satélite LANDSAT 7.

Parallel Networks for Machine Vision

The amount of computation required to solve many early vision problems is prodigious, and so it has long been thought that systems that operate in a reasonable amount of time will only become feasible when parallel systems become available. Such systems now exist in digital form, but most are large and expensive. These machines constitute an invaluable test-bed for the development of new algorithms, but they can probably not be scaled down rapidly in both physical size and cost, despite continued advances in semiconductor technology and machine architecture. Simple analog networks can perform interesting computations, as has been known for a long time. We have reached the point where it is feasible to experiment with implementation of these ideas in VLSI form, particularly if we focus on networks composed of locally interconnected passive elements, linear amplifiers, and simple nonlinear components. While there have been excursions into the development of ideas in this area since the very beginnings of work on machine vision, much work remains to be done. Progress will depend on careful attention to matching of the capabilities of simple networks to the needs of early vision. Note that this is not at all intended to be anything like a review of the field, but merely a collection of some ideas that seem to be interesting.

A Comparison of Hardware Implementations for Low-Level Vision Algorithms

Early and intermediate vision algorithms, such as smoothing and discontinuity detection, are often implemented on general-purpose serial, and more recently, parallel computers. Special-purpose hardware implementations of low-level vision algorithms may be needed to achieve real-time processing. This memo reviews and analyzes some hardware implementations of low-level vision algorithms. Two types of hardware implementations are considered: the digital signal processing chips of Ruetz (and Broderson) and the analog VLSI circuits of Carver Mead. The advantages and disadvantages of these two approaches for producing a general, real-time vision system are considered.

Detecting Digital Forgeries Using Bispectral Analysis

With the rapid increase in low-cost and sophisticated digital technology the need for techniques to authenticate digital material will become more urgent. In this paper we address the problem of authenticating digital signals assuming no explicit prior knowledge of the original. The basic approach that we take is to assume that in the frequency domain a "natural" signal has weak higher-order statistical correlations. We then show that "un-natural" correlations are introduced if this signal is passed through a non-linearity (which would almost surely occur in the creation of a forgery). Techniques from polyspectral analysis are then used to detect the presence of these correlations. We review the basics of polyspectral analysis, show how and why these tools can be used in detecting forgeries and show their effectiveness in analyzing human speech.

Relevo digital dos municípios brasileiros.

2008

An Analog VLSI Chip for Estimating the Focus of Expansion

For applications involving the control of moving vehicles, the recovery of relative motion between a camera and its environment is of high utility. This thesis describes the design and testing of a real-time analog VLSI chip which estimates the focus of expansion (FOE) from measured time-varying images. Our approach assumes a camera moving through a fixed world with translational velocity; the FOE is the projection of the translation vector onto the image plane. This location is the point towards which the camera is moving, and other points appear to be expanding outward from. By way of the camera imaging parameters, the location of the FOE gives the direction of 3-D translation. The algorithm we use for estimating the FOE minimizes the sum of squares of the differences at every pixel between the observed time variation of brightness and the predicted variation given the assumed position of the FOE. This minimization is not straightforward, because the relationship between the brightness derivatives depends on the unknown distance to the surface being imaged. However, image points where brightness is instantaneously constant play a critical role. Ideally, the FOE would be at the intersection of the tangents to the iso-brightness contours at these "stationary" points. In practice, brightness derivatives are hard to estimate accurately given that the image is quite noisy. Reliable results can nevertheless be obtained if the image contains many stationary points and the point is found that minimizes the sum of squares of the perpendicular distances from the tangents at the stationary points. The FOE chip calculates the gradient of this least-squares minimization sum, and the estimation is performed by closing a feedback loop around it. The chip has been implemented using an embedded CCD imager for image acquisition and a row-parallel processing scheme. A 64 x 64 version was fabricated in a 2um CCD/ BiCMOS process through MOSIS with a design goal of 200 mW of on-chip power, a top frame rate of 1000 frames/second, and a basic accuracy of 5%. A complete experimental system which estimates the FOE in real time using real motion and image scenes is demonstrated.

Mapeamento digital de classes e atributos de solos: métodos, paradigmas e novas técnicas.

Panorama geral sobre os métodos de mapeamento de solos e/ou de suas propriedades, assim como sobre as principais técnicas quantitativas usadas.

Extração de variáveis topográficas do modelo digital de elevaçao SRTM para o estado do Rio de Janeiro

2005

The Coupled Depth/Slope Approach to Surface Reconstruction

Reconstructing a surface from sparse sensory data is a well known problem in computer vision. Early vision modules typically supply sparse depth, orientation and discontinuity information. The surface reconstruction module incorporates these sparse and possibly conflicting measurements of a surface into a consistent, dense depth map. The coupled depth/slope model developed here provides a novel computational solution to the surface reconstruction problem. This method explicitly computes dense slope representation as well as dense depth representations. This marked change from previous surface reconstruction algorithms allows a natural integration of orientation constraints into the surface description, a feature not easily incorporated into earlier algorithms. In addition, the coupled depth/ slope model generalizes to allow for varying amounts of smoothness at different locations on the surface. This computational model helps conceptualize the problem and leads to two possible implementations- analog and digital. The model can be implemented as an electrical or biological analog network since the only computations required at each locally connected node are averages, additions and subtractions. A parallel digital algorithm can be derived by using finite difference approximations. The resulting system of coupled equations can be solved iteratively on a mesh-pf-processors computer, such as the Connection Machine. Furthermore, concurrent multi-grid methods are designed to speed the convergence of this digital algorithm.

Probabilistic Solution of Inverse Problems

In this thesis we study the general problem of reconstructing a function, defined on a finite lattice from a set of incomplete, noisy and/or ambiguous observations. The goal of this work is to demonstrate the generality and practical value of a probabilistic (in particular, Bayesian) approach to this problem, particularly in the context of Computer Vision. In this approach, the prior knowledge about the solution is expressed in the form of a Gibbsian probability distribution on the space of all possible functions, so that the reconstruction task is formulated as an estimation problem. Our main contributions are the following: (1) We introduce the use of specific error criteria for the design of the optimal Bayesian estimators for several classes of problems, and propose a general (Monte Carlo) procedure for approximating them. This new approach leads to a substantial improvement over the existing schemes, both regarding the quality of the results (particularly for low signal to noise ratios) and the computational efficiency. (2) We apply the Bayesian appraoch to the solution of several problems, some of which are formulated and solved in these terms for the first time. Specifically, these applications are: teh reconstruction of piecewise constant surfaces from sparse and noisy observationsl; the reconstruction of depth from stereoscopic pairs of images and the formation of perceptual clusters. (3) For each one of these applications, we develop fast, deterministic algorithms that approximate the optimal estimators, and illustrate their performance on both synthetic and real data. (4) We propose a new method, based on the analysis of the residual process, for estimating the parameters of the probabilistic models directly from the noisy observations. This scheme leads to an algorithm, which has no free parameters, for the restoration of piecewise uniform images. (5) We analyze the implementation of the algorithms that we develop in non-conventional hardware, such as massively parallel digital machines, and analog and hybrid networks.