基于DSP的CIS信号采集与处理技术

CIS(接触式图像传感器)是一种新型图像传感器。介绍了CIS的主要结构、特点和工作原理，提出了一种基于DSP的CIS信号采集与处理方案。与传统的图像采集系统相比，该系统由于采用CIS作为图像传感器，DSP作为控制和运算核心，因而具有电路简单，控制方便的特点。最后，给出了该系统在实际应用中的工作波形。     

一种新型高速智能视觉传感器的设计与实现

视觉传感器与DSP和FPGA相结合，构建了一种集图像采集和处理于一体的高速智能视觉传感器。FPGA的使用使图像处理硬件化，大大提高了图像采集处理速度；DSP的运用使传感器可以拥有自己的CPU，并可以进行一些复杂的运算，因而更加智能化，网络化。     

热成像传感器动静态成像系统设计

为测试研究室开发的热成像传感器性能与成像质量,设计了成像传感器动静态成像与图像算法验证系统.系统能够捕获成像传感器静态图像,并能实时成像,具有通用性.数据的采集和处理应用FPGA+ DSP开发板实现.数据传输基于CY7C68013芯片以块同步数据传输方式,实现了无缝同步方式高速传输.基于VS2010编程环境和开源机器视觉库编写了接收、存储以及处理图像数据应用程序平台.测试表明:系统能够以40 Mbyte/s速率数据传输,用于实验室开发的热成像传感器工作良好.     

基于DSK的图像处理算法仿真系统

在DSP系统开发的过程中，图像处理算法的设计、调试是一个复杂的过程，一般是在软件上进行仿真。采用基于DSK(DSP初学者套件)的图像处理系统进行图像处理，算法的硬件仿真与性能评估，使得算法直接在DSP芯片上运行，可以得到最直接的性能评估参数，同时避免了进行程序从软件到DSP芯片的移植过程，使开发人员可以将精力集中在算法的设计和改进上，大大提高开发效率，保证了最终系统的可靠性和稳定性。     

PET瓶封盖质量在线检测系统的设计与实现

设计了一套完整的基于DSP+ARM双核处理器的PET瓶封盖质量检测系统。首先通过DSP DM642完成对图像传感器MT9P031的RAW原始数据采集,然后对采集的PET瓶图像进行定位并实现相关的图像处理算法,最后采用ARM11嵌入式系统对整个传动设备进行监控。经过实际生产线的应用证明,该在线检测系统能够胜任在高速PET瓶封盖生产线中的应用。     

一种实用的多目立体视觉系统设计方法

1引言 立体视觉是获取物体三维形状信息的重要方法之一,已经在工业测量、物体建模、视觉导航和物体识别等领域得到了广泛的应用.目前的立体视觉系统通常由多个摄像机、图像采集卡、外同步信号控制以及多路转换器等组成,系统复杂、成本高,操作不方便,限制了立体视觉技术在实际中的应用.本文基于CMOS图像传感器和IEEE 1394总线接口技术,探讨了一种实时、低成本、简单可靠的多目立体视觉系统的设计与实现方法.我们认为,随着CMOS图像传感器成像质量的不断提高,本文提出的视觉系统设计方法会得到越来越广泛的应用.     

感知特征互补的图像质量评价

针对图像质量客观评价方法在实际应用场景下性能退化的问题,将人眼视觉特性融入图像特征处理的多个环节,提出一种融合视觉结构显著和视觉能量显著特征互补的方法。首先,根据人眼特性对图像的灰度能量、对比度能量和梯度结构三层互补特征进行空域-频域联合变换处理;其次,分别提取前述三层视觉特征的多通道信息并进行评价;最后,基于视觉特性和图像失真度将各层视觉特征评价从内层至外层逐步自适应综合。实验表明,本方法具有较高的水平和更好的稳定性,提高了实际应用场景下的评价性能。     

智能图像检测在活塞在线分选中的应用

基于某活塞生产厂的活塞在线检测需求本文将机器视觉检测技术应用于活塞在线视觉检测分选中,开发出一套智能图像检测系统.该系统将VB与图像传感器相结合,充分利用VB和智能图像传感器的特点,使检测系统操作简单、高效精确.在检测中,主要应用了模板匹配原理对图像进行识别.该图像检测系统满足了生产实际的需求,提高了生产效率,减轻了工人的劳动强度,实现了活塞的在线检测与分选.     

基于FPGA和DSP的车牌识别系统的研究

针对常见的车牌识别系统依赖上位机成本高,并且体积较大不利于野外工作的问题,采用了一种以DSP和FPGA为开发平台的车牌识别系统的设计方案;利用FPGA控制CMOS图像传感器进行车牌图像数据的采集,经过图像格式转换之后传送到DSP中,进行车牌区域定位、字符分割、车牌识别等操作,最后将识别结果传送到LCD中显示;系统采用CCS(Code Composer Studio)集成开发环境,利用VC++语言编程实现车牌识别算法;通过嵌入式机器视觉库EMCV实现识别算法在DSP中的移植,并在LCD上创建工作窗口显示识别结果,检测速度快,准确率高;实验结果表明,该车牌识别系统的设计方案识别结果准确,功能稳定可靠,有效地解决了常见车牌识别系统成本高,体积大不利于野外工作的问题,达到了设计目的。     

星上DSP系统性能提高的瓶颈及其对策

本文针对执行数据处理任务的星上应用DSP系统，以系统设计的角度，从外部存储器速度、外部存储器容量、软件可靠性三方面详细分析了限制DSP系统进一步提高性能的瓶颈，并分别提出了解决方案。应用这些方案到实际的星上DSP系统设计中，将大幅度的提高数据处理性能，提高DSP芯片在星上应用的可靠性。     

BETWEEN LOCATION AWARENESS AND AWARE LOCATIONS: WHERE TO PUT THE INTELLIGENCE

This article presents a review on vision-aided systems and proposes an approach for visual rehabilitation using stereo vision technology. The proposed system utilizes stereo vision, image processing methodology, and a sonification procedure to support blind mobilization. The developed system includes wearable computer, stereo cameras as vision sensor, and stereo earphones, all molded in a helmet. The image of the scene in front of the visually handicapped is captured by the vision sensors. The captured images are processed to enhance the important features in the scene in front for mobilization assistance. The image processing is designed as a model of human vision by identifying the obstacles and their depth information. The processed image is mapped onto musical stereo sound for the blind's understanding of the scene in front. The developed method has been tested in the indoor and outdoor environments and the proposed image processing methodology is found to be effective for object identification.     

用于移动机器人的视觉全局定位系统研究

本文叙述了用于移动机器人自主导航定位的一种视觉全局定位系统技术．该视觉定 位系统由LED主动路标、全景视觉传感器和数据处理系统组成．本文主要介绍了为提高全景 视觉图像处理速度和环境信标识别可靠性、准确性的应用方法,并给出了实验结果．实验表 明,视觉定位是具有明显研究价值和应用前景的全局导航定位技术．     

Robot vision: An evaluation of imaging sensors

Robot vision, robotics vision, and computer vision are terms that have evolved over the past few years to include two separate but related functions that provide visual sensing for computerdriven robots. These two functions are “electro-optical imaging” and “image processing.” The purpose of electro-optical imaging is to convert optical radiation to an appropriate electronic signal for input to the robot's computer; whereas, the purpose of image processing is to extract useful information from the electronic image provided by the sensor. This article deals with the electro-optical sensing part of robot vision. It describes the operation and properties of electro-optical imaging sensors. The fundamental concepts of optical radiation, optical radiation quantities and units, and photon energies are defined. The fundamental principles for detecting optical radiation and definitions for the primary performance measures for optical detectors are given. A relatively comprehensive overview of the parameters used to describe imaging sensors is presented. Factors affecting these parameters and obtainable sensor performance are compared. Example design analyses are presented to show the interaction of various performance measures.     

健康服务机器人室内导航视觉传感器研究与开发*

针对健康服务机器人室内导航的应用需求,设计出一种基于STM32F429的嵌入式导航视觉传感器,内嵌500万像素CMOS图像传感器和拥有高性能无线SOC的ESP8266,此次开发的视觉传感器,不是一般的CMOS图像传感器,而是综合了图像感知,图像处理,无线通信,节电唤醒等等功能于一体的智能化微型装置,即眼睛加大脑。经测试,本导航视觉传感器能够以每秒3次的速度向服务机器人发送位置,完全满足室内移动机器人的移动需求。     

非接触式机器人直线轨迹测量系统

视觉的、造价低廉实用的非接触式机器人直线轨迹测量系统．该测量系统由结构光视觉传感 器、测量轨道、主控计算机及相关软件组成．视觉传感器可固定于机器人末端．当机器人末 端带动视觉传感器沿测量轨道做直线运动时，通过传感器测量相对测量轨道的连续位姿关系 ，就可间接描述机器人末端的运动轨迹．当重复同一直线运动时，可检测出机器人的轨迹重 复性．本文综述了机器人直线轨迹测量设备的研究现状，介绍了轨迹检测系统的测量原 理，重点讨论了该测量系统的两个关键技术：空间特征点的图象提取技术和三维坐标计算方 法，并描述了该系统的结构、性能指标和测量试验结果．     

Fuzzy image processing scheme for autonomous navigation of human blind

The main objective of this work is to develop an electronic travel aid to assist the blinds for obstacle identification in their navigation. This navigation assistance for visually impaired (NAVI) system presented in this paper consists of a single board processing system (SBPS), a vision sensor mounted headgear and a pair of stereo earphones. The image environment in front of the blind is captured by the vision sensor. The image is processed by a new real time image processing scheme using fuzzy clustering algorithms. The processed image is mapped onto a specially structured stereo acoustic patterns and transferred to the stereo earphones in the system. Blind individuals were trained with NAVI system and tested for obstacle identification. Suggestions from the blind volunteers regarding pleasantness and discrimination of sound pattern were also incorporated in the prototype. The proposed processing methodology is found to be effective for object identification and for producing stereo sound patterns in the NAVI system.     

Stereo vision system for moving object detecting and locating based on CMOS image sensor and DSP chip

Currently, most of the stereo vision systems are constructed on PC-based or multi-CPU combination structures with two CCD cameras. It is difficult to be applied in movable plants for stand-alone requirement. Due to electronic technology development, the complementary metal-oxide semiconductor (CMOS) image sensor has been widely used in a lot of electronic commercial products and the digital signal processor (DSP) operation speed and capacity are good enough for stereo vision system requirement. Here, a new stereo vision platform is designed with TMS320C6416 DSK board integrated with two CMOS color image sensors for detecting and locating moving objects. The data communication interface, system monitoring timing flow, and image pre-processing software programs are developed, too. This system can be used to detect and track any moving object without object color and shape limitations of previous study. Experimental results are used to evaluate this system’s dynamic performance. This low cost stereo vision system can be employed in movable platform for stand-alone application, i.e., mobile robot.     

Comparison of image processing algorithms and neural networks in machine vision inspection

Automated vision inspection has become a vital part of the computer integrated manufacturing systems. This paper compares the development and performance of two methodologies for a machine vision inspection system. The first method is developed through conventional image processing algorithms and the second method is based on the neural networks. A case study was conducted to benchmark these two methods. The results showed that the conventional image processing algorithms required less development time than the neural networks. A considerable amount of time was spend on training the neural networks. However, the neural networks performed better than the conventional image processing algorithms in terms of accuracy.     

CCD camera modeling and simulation

In this paper we propose a modeling of an acquisition line made up of a CCD camera, a lens and a frame grabber card. The purpose of this modeling is to simulate the acquisition process in order to obtain images of virtual objects. The response time has to be short enough to permit interactive simulation. All the stages are modelised: in the first phase, we present a geometric model which supplies a point to point transformation that provides, for a space point in the camera field, the corresponding point on the plane of the CCD sensor. The second phase consists of modeling the discrete space which implies passing from the continous known object view to a discrete image, in accordance with the different orgin of the contrast loss. In the third phase, the video signal is reconstituted in order to be sampled by the frame grabber card. The practical results are close to reality when compared to image processing. This tool makes it possible to obtain a short computation time simulation of a vision sensor. This enables interactivity either with the user or with software for the design/simulation of an industrial workshop equipped with a vision system. It makes testing possible and validates the choice of sensor placement and image processing and analysis. Thanks to this simulation tool, we can control perfectly the position of the object image placed under the camera and in this way, we can characterise the performance of subpixel accuracy determining methods for object positioning.