Video processing on dsp
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This document discusses using MATLAB and a DSP processor for image processing and computer vision applications. It describes how MATLAB can be used to acquire images, analyze image content, and control actuators. However, image processing requires significant computational resources, so the code is run on a computer connected to a webcam rather than a microcontroller. The Texas Instruments TMS320C6713 DSK platform allows MATLAB codes to be implemented on a DSP processor for these types of applications. Example applications mentioned include medical imaging, object recognition, and robotic vision.
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The following resources come from the 2009/10 B.Sc in Media Technology and Digital Broadcast (course number 2ELE0073) from the University of Hertfordshire. All the mini projects are designed as level two modules of the undergraduate programmes.التلفزيون الرقمي التعليمي Instructional Digital Television
التلفزيون الرقمي التعليمي Instructional Digital TelevisionProfessional Diploma in Education - Department of Education Technology
التلفزيون الرقمي هو برامج تلفزيونية رقمية، مخططة ومنظمة ومنتظمة، تبث عبر قنوات رقمية أو إلكترونية، لتحقيق أهداف تعليمية محددة ترتبط مباشرة ببرامج ومقررات دراسية معينة لدى فئة محددة من المتعلمين أو الدارسين.
ما هي فوائد التلفزيون الرقمي؟
العديد من مشاهدي التلفزيون بدئوا هذه الأيام يتحولون من النظام القديم ذو التقنية التناظرية (الأساسية للتلفزيون والتي عرفت منذ أيام الحرب العالمية الثانية) إلى التقنية الرقمية الحديثة, فحصلوا بذلك على صور أوضح بكثيرة مما كانوا يحصلون عليها بالتلفزيون القديم ذو التقنية التناظرية.
وبالنسبة لمستخدمي هذه الخدمة قد تكون هي أفضل مزية للتلفزيون الرقمي وهذا هو ليس السبب الوحيد, ففي التلفزيون الرقمي الجديد سوف لن يكون هناك أشباح بالتلفزيون الرقمي ولا ثلج متساقط في الصورة كما كان دائما في التلفزيون التناظري القديم وبذلك سيعطي التلفزيون الرقمي الصورة المثالية, كما سيسمح التلفزيون الرقمي بإنتاج وتقديم شاشات أوسع أيضا, وبذلك أصبحت مشاهدة التلفزيون متعة حقيقية كما لو كانت مشاهدة حية في المسرح أو في صالة السينما.
لكن هذا ليس كل فوائد ومزايا البث الرقمي و التلفزيون الرقمي فمن طبيعة هذا النظام الرقمي استخدام موجة أصغر و ذلك يعني بأنه يمكن عصر عدة محطات للبث التلفزيوني على نفس طيف الإذاعي Broadcasting Spectrum، أو سيمكن الكيبل من حمل محطات أكثر ولخدمات أخرى متعددة.
الموجة المخفضة للتلفزيون الرقمي سيسمح للحكومة بتخصيص ترددات البث التلفزيوني السابقة إلى الاستعمالات الأخرى، مثل خدمات الإنترنت اللاسلكي.
مع كل النواحي الإيجابية للنظام الرقمي، هناك نقطة سلبية واحدة ولكنها مهمة، فعلى أية حال بالنسبة للبث الهوائي عبر الأثير سيستلم الناس إشاراتهم على الهواء وسيجدون بأن الصورة المستلمة دائما ستكون مثالية أو ستكون معدومة ولن يجدونها مطلقا, وذلك عند ضعف الإشارة أو يوجد ما يضعفها, ففي التلفزيون المتناظر، من المحتملWavelet
The document introduces the limitations of Fourier transforms for analyzing non-stationary signals and discusses how wavelet transforms provide a solution. Fourier transforms can only provide frequency content over the entire signal duration and cannot localize this content in time. Wavelet transforms overcome this by analyzing the signal with translated and scaled versions of an analyzing wavelet, allowing time-frequency localization. This provides a time-frequency representation of non-stationary signals and indicates when different frequency components occur.
Progressive Enhancement 2.0 (Conference Agnostic)
In the beginning, progressive enhancement was simple: HTML layered with CSS layered with JavaScript. That worked fine when there were two browsers, but in today's world of multiple devices and multiple browsers, it's time for a progressive enhancement reboot. At the core is the understanding that the web is not print - the same rules don't apply. As developers and consumers we've been fooled into thinking about print paradigms for too long. In this talk, you'll learn just how different the web is and how the evolution of progressive enhancement can lead to better user experiences as well as happier developers and users.
This deck is a conference-agnostic one, suitable to be shown anywhere without site-specific jokes!
Video editing presentation
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WBAN
This document provides an overview of a senior design project to create a prototype wireless body area network (WBAN) consisting of a custom body sensor unit (BSU) and an Android-based body control unit (BCU). The BSU hardware prototype measures motion data from an accelerometer and gyroscope, timestamps the data, transmits it to the BCU via Bluetooth, and stores 30 minutes of data locally. The BCU is an Android phone running a custom app that receives the data, stores 8 hours of data locally, and allows the user to view the data. The project aimed to design compact, lightweight, long-lasting devices to monitor patients and help reduce healthcare costs through remote monitoring.
Wireless Body Area Network (WBAN)
This presentation provides an overview of wireless body area networks (WBANs) including:
- WBANs use wireless networking technology to interconnect sensors on or in the human body to monitor physiological data.
- A typical WBAN consists of multiple sensor nodes measuring data like ECG, blood pressure, motion that communicate wirelessly.
- Challenges for WBANs include hardware limitations, security of medical data, and limited battery life of sensor nodes.
- WBANs have applications in remote health monitoring and medical research through projects like MobiHealth.
Wavelet
The document discusses performing a discrete wavelet transform (DWT) on a 1D signal using MATLAB. It loads a test signal, performs a 5-level DWT decomposition using the coif3 wavelet, then reconstructs the approximation and detail signals at each level. Plots of the original, approximation, and detail signals are generated.
Introduction to Wavelet Transform with Applications to DSP
Introduction to wavelet transforms.
History,
Mathematical development,
Applications in digital signal processing.
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Wireless body area network
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Matlab Introduction
A basic overview, application and usage of MATLAB for engineers. It covered very basics essential that will help one to get started with MATLAB programming easily.
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Introduction to wavelet transform
This document provides an introduction to wavelet transforms. It begins with an outline of topics to be covered, including an overview of wavelet transforms, the limitations of Fourier transforms, the historical development of wavelets, the principle of wavelet transforms, examples of applications, and references. It then discusses the stationarity of signals and how Fourier transforms cannot show when frequency components occur over time. Short-time Fourier analysis is introduced as a solution, but it is noted that wavelet transforms provide a more flexible approach by allowing the window size to vary. The document proceeds to define what a wavelet is, discuss the historical development of wavelet theory, provide examples of popular mother wavelets, and explain the steps to compute a continuous wave
wireless body area networks(WBAN)
This document outlines a proposed wireless body area network (WBAN) system for ubiquitous and affordable healthcare. It begins with an introduction to WBANs and their use in continuous health monitoring. A 3-tier network architecture is proposed, consisting of wearable sensor nodes, a personal server, and a medical server. The document discusses the existing holter monitor system, proposed WBAN system capabilities, data flow, network positioning, system requirements, security considerations, applications, and comparisons to other wireless networks. Potential advantages include remote health monitoring and early disease detection, while challenges include interference between devices and lack of sensor integration.
discrete wavelet transform
This document summarizes a student project on implementing lossless discrete wavelet transform (DWT) and inverse discrete wavelet transform (IDWT). It provides an overview of the project, which includes introducing DWT, reviewing literature on lifting schemes for faster DWT computation, and simulating a 2D (5,3) DWT. The results show DWT blocks decomposing signals into high and low pass coefficients. Applications mentioned are in medical imaging, signal denoising, data compression and image processing. The conclusion discusses the need for lossless transforms in medical imaging. Future work could extend this to higher level transforms and applications like compression and watermarking.
Wavelet based image compression technique
This document summarizes a presentation on wavelet based image compression. It begins with an introduction to image compression, describing why it is needed and common techniques like lossy and lossless compression. It then discusses wavelet transforms and how they are applied to image compression. Several research papers on wavelet compression techniques are reviewed and key advantages like higher compression ratios while maintaining image quality are highlighted. Applications of wavelet compression in areas like biomedicine and multimedia are presented before concluding with references.
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Automatic License Plate Recognition system is a real time embedded system which automatically recognizes the license plate of vehicles. There are many applications ranging from complex security systems to common areas and from parking admission to urban traffic control. Automatic license plate recognition (ALPR) has complex characteristics due to diverse effects such as of light and speed. Most of the ALPR systems are built using proprietary tools like Matlab. This paper presents an alternative method of implementing ALPR systems using Free Software including Python and the Open Computer Vision Library.
Automatic License Plate Recognition using OpenCV
Automatic License Plate Recognition system is a real time embedded system which automatically recognizes the license plate of vehicles. There are many applications ranging from complex security systems to common areas and from parking admission to urban traffic control. Automatic license plate recognition (ALPR) has complex characteristics due to diverse effects such as of light and speed. Most of the ALPR systems are built using proprietary tools like Matlab. This paper presents an alternative method of implementing ALPR systems using Free Software including Python and the Open Computer Vision Library.
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Lead embedded this a startup company start in June 2021
1.LEAD EMBEDDED SPECIALIZES IN SOFT WARE DEVELOPMEAT FOR CAN EOL TOOLS USING IN UDS AND OBD2 PROTOCOLS IN AUTOMOTIVE VEHICLES .
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Pradeep Prasad is seeking software development opportunities starting in May 2016. He has a Master's degree in Electrical and Computer Engineering from the University of Arizona and a Bachelor's degree in Telecommunication Engineering. He has strong programming skills in C, C++, Java, VHDL, and Verilog. He has experience with tools like Xilinx, Microvision IDE, and Linux. His academic projects include designing cache architectures, developing intrusion detection systems, and creating scheduling and synthesis tools.
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Ganesh Sankar has over 15 years of experience in automotive embedded software development. He currently works as a senior technical lead for HCL GmbH, where he is responsible for microcontroller abstraction layer configuration, BSW modules configuration, and complex device driver development. Previously, he held roles as a senior software engineer at Robert Bosch and as a software engineer at WABCO TVS, where he gained experience developing embedded software for instrument clusters, air suspension systems, and active vehicle height sensors. He also has experience developing DRM digital radio systems as a senior engineer at Jasmin Infotech.
Dipak_Desai_Resume
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Prasad_CTP
The document provides a summary of an experienced software engineer with over 10 years of experience in systems engineering, real-time software development, testing and project consulting. The engineer has expertise in model-based development, systems engineering, testing and collaboration tools from IBM Rational. Several projects are summarized involving development of combat management systems, model-based systems engineering, model-driven development, collaborative lifecycle management and static analysis.
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This implemented DSP system utilizes TCP socket communication. Upon message reception, it decides the appropriate process to be executed based on cases which can be categorized as follows:
1) image capture
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A user-friendly MATLAB GUI, named DIPeth, facilitates the system's control.Portfolio of Projects
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For additional information:
https://www.pmprofessional.ch
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Rashmi_Resume
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This document describes the design of an optical character recognition (OCR) toolbox for decoding vehicle number plates using MATLAB. It involves four main parts: 1) Designing the OCR toolbox which includes template creation and letter detection. 2) Checking if the number plate has single or double layers. 3) Applying a detection of vehicle number (DVN) algorithm to process the image and recognize characters. 4) Creating a database in Excel to store the vehicle registration details retrieved from OCR and allowing lookup of owner information. The proposed method achieved 96% accuracy on 50 tested number plates. It can potentially help applications like automatic toll collection and traffic monitoring.
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Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Rainfall intensity duration frequency curve statistical analysis and modeling...
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
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#Abstract:
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#Prerequisites:
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Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
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本公司拥有海外各大学样板无数，能完美还原海外各大学 Bachelor Diploma degree, Master Degree Diploma
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2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
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6:个人职称评审加20分
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- 2. MATLAB CCS TMS320 Family Application Reference A vision based project has an image acquisition device like a webcam as its eyes. Then we need a processor that can make sense out of those captured images and actuators. One key point to note is that Image Processing has huge computational requirements, and it is not possible to run an image processing code directly on a small microcontroller. Hence, for our purpose, the simplest approach would be to run the code on a computer, which has a webcam connected to it to take the images, and the robot is controlled by the computer via serial or parallel port. The code is written in a software that provides the tools for acquiring images, analyzing the content in the images and deriving conclusions. MATLAB is one of the many such software available which provide the platform for performing these tasks.
- 4. Imaq.videodevice vid=videoinput('winvideo',1, ‘RGB_160x120') preview(vid) vision.VideoPlayer Vision.shapeinserter Vision.textinserter
- 5. -Modeling/designing dynamic systems (including nonlinear dynamics) -Modeling/designing control systems (including nonlinear controllers and plants) -Signal processing design/simulation
- 6. Colour detection and tracking on matlab Making Static Shape Making Dynamic Shape as per our requirement Remote accessing Playing Games
- 7. CCS is TI’s proprietary IDE that provides a transition between a high-level DSP program and an on-board machine language program. It is used to: Generate programs for the C6713 DSP using C language, Load them into the DSK, Run them, Monitor program execution. 7
- 9. 1.Software development tools such as assembler, linkers , simulators and compilers 2.DSP boards for software development and testing before target DSP hardware is available 3.Hardware testing tool such as emulator and logic analyzers. 4.Development assistance such as application libraries , real time debugging hardware available
- 10. The Texas Instruments C6713 DSK platform, which can be programmed using SIMULINK. This gives us added advantage of easily writing codes on MATLAB and implementing it on the DSP processors. Based on a very-long-instruction-word (VLIW) architecture, the C6x is considered to be TI’s most powerful processor.
- 13. Medical Imaging Object Recognition Color Image Processing Industrial Machine Vision for product assembly Automated Target detection and tracking Finger Print, Facial Recognition Systems Robotic Vision Autonomous robots and autonomous vehicles
- 14. [1]. MATLAB Documentation: http://www.mathworks.com/help/techdoc/ [2] Texas Instruments, TMS320C6713B, Floating-Point Digital Signal Processors, Data Sheet,Dallas, TX, June 2006 [3] D. R. Brown III, 2009 Workshop on Digital Signal Processing and Applications with the TMS320C6713 http://spinlab.wpi.edu/courses/dspworkshop/dspworkshop _part1_2009.pdf