The Image Acquisition Toolbox allows users to acquire images and video directly into MATLAB and Simulink from various imaging hardware. It provides features such as automatically detecting hardware, configuring device properties, previewing acquisitions, and acquiring images and video from supported devices. The toolbox also enables incorporating image acquisition into Simulink models and developing customized imaging applications in MATLAB.
Learn about the Smart Virtual Appliances Made Easy with IBM Image Construction and Composition Tool. The IBM Image Construction and Composition Tool can be used to construct custom virtual appliances that can be provisioned with several cloud deployment platforms. This IBM Redbooks Solution Guide introduces the IBM Image Construction and Composition Tool and provides an overview if its features, benefits, and architecture. For more information on IBM Systems, visit http://ibm.co/RKEeMO.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
This document provides information about hardware and software used for graphic design. It discusses topics like digital visual interfaces, color depth, integrated vs dedicated graphics cards, memory, processors, storage devices, input/output devices, file formats, and image editing software. Key points include that DVI connects graphics cards to monitors, color depth refers to the number of available colors, integrated graphics are built into the motherboard while dedicated cards install separately, and RAM is used for temporary storage of open graphic files.
The document describes an image exploitation system developed for airborne surveillance using unmanned aerial vehicles. The system processes real-time video and flight data acquired by the UAV. It uses image processing algorithms like enhancement, filtering, target tracking, and geo-referencing of targets. The system displays mission parameters in real-time on multiple displays. It was found to be qualified for surveillance applications. Sample results are presented.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
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.
The document discusses real-time image processing and different approaches for acquiring and processing images and video in real-time. It compares libraries and frameworks like OpenCV, DirectShow, and Vision SDK. OpenCV is highlighted as it provides both high-level and low-level functions for tasks like image acquisition, processing, and display and has become popular for real-time applications due its open source nature and support. Sample code in OpenCV is also provided to demonstrate a basic real-time video processing application.
시크 SICK Lector63x 2D DPM스캐너 고정식바코드스캐너 산업용바코드리더 이미지스캐너 매뉴얼HION IT
The document provides instructions for setting up and operating the Lector632 Flex image-based code reader. It describes mounting the reader, connecting it, and configuring it using the SOPAS Engineering Tool software. The configuration involves setting image acquisition parameters, code reading settings, and output formatting. Dimensional drawings, connection diagrams, and technical specifications are also included.
Learn about the Smart Virtual Appliances Made Easy with IBM Image Construction and Composition Tool. The IBM Image Construction and Composition Tool can be used to construct custom virtual appliances that can be provisioned with several cloud deployment platforms. This IBM Redbooks Solution Guide introduces the IBM Image Construction and Composition Tool and provides an overview if its features, benefits, and architecture. For more information on IBM Systems, visit http://ibm.co/RKEeMO.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
This document provides information about hardware and software used for graphic design. It discusses topics like digital visual interfaces, color depth, integrated vs dedicated graphics cards, memory, processors, storage devices, input/output devices, file formats, and image editing software. Key points include that DVI connects graphics cards to monitors, color depth refers to the number of available colors, integrated graphics are built into the motherboard while dedicated cards install separately, and RAM is used for temporary storage of open graphic files.
The document describes an image exploitation system developed for airborne surveillance using unmanned aerial vehicles. The system processes real-time video and flight data acquired by the UAV. It uses image processing algorithms like enhancement, filtering, target tracking, and geo-referencing of targets. The system displays mission parameters in real-time on multiple displays. It was found to be qualified for surveillance applications. Sample results are presented.
ER Publication,
IJETR, IJMCTR,
Journals,
International Journals,
High Impact Journals,
Monthly Journal,
Good quality Journals,
Research,
Research Papers,
Research Article,
Free Journals, Open access Journals,
erpublication.org,
Engineering Journal,
Science Journals,
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.
The document discusses real-time image processing and different approaches for acquiring and processing images and video in real-time. It compares libraries and frameworks like OpenCV, DirectShow, and Vision SDK. OpenCV is highlighted as it provides both high-level and low-level functions for tasks like image acquisition, processing, and display and has become popular for real-time applications due its open source nature and support. Sample code in OpenCV is also provided to demonstrate a basic real-time video processing application.
시크 SICK Lector63x 2D DPM스캐너 고정식바코드스캐너 산업용바코드리더 이미지스캐너 매뉴얼HION IT
The document provides instructions for setting up and operating the Lector632 Flex image-based code reader. It describes mounting the reader, connecting it, and configuring it using the SOPAS Engineering Tool software. The configuration involves setting image acquisition parameters, code reading settings, and output formatting. Dimensional drawings, connection diagrams, and technical specifications are also included.
IBM's SmartCloud Orchestrator provides end-to-end automation of cloud service delivery through workload orchestration, resource orchestration, and service orchestration. It integrates with existing data center tools and processes using open standards. The Orchestrator includes content types like software bundles, virtual images, and patterns to automate multi-tier application deployments. It also allows custom orchestration operations through actions, user interfaces, and service offerings.
LightWave 3D 11 is a 3D modeling, rendering and animation software. It offers features like instancing for mass object duplication, Bullet physics engine for realistic simulations, fracture tools for breaking 3D objects, flocking tools for natural crowd behaviors, and iridescent car paint shaders for realistic materials. LightWave 11 also enhances its interchange with ZBrush for sculpting details and improves its rendering tools and user interface for faster workflows.
Matrox Design Assistant is a flowchart-based machine vision software that allows users to create vision applications without writing code. It provides an intuitive integrated development environment where applications are built by constructing a flowchart using visual tools for image processing, measurement, pattern matching, and more. The software also enables users to design a web-based operator interface. It supports a wide range of GigE and USB3 cameras and can deploy applications to Matrox vision systems and smart cameras.
Visual Studio 2008 provides tools for code editing, debugging, and building applications. It includes an integrated development environment with support for multiple programming languages like C#, VB, and C++. The IDE can be customized with a variety of settings and options. It also provides a project system to manage code components and references across one or more projects in a solution.
This document provides a summary of Amit Prabhudesai's work portfolio. It outlines his educational background and work experience in image processing and computer vision. It then describes several projects he has worked on, including human detection using Adaboost for surveillance video, optimizing a Lane Departure Warning system for a Texas Instruments DSP, developing video analytics software for retail store customer counting and queue detection, and an Automatic Fingerprint Identification System. It also lists some relevant trainings and mentorship activities.
An Instantaneous Introduction to the Alliance Access GridVideoguy
The document summarizes the Access Grid, a model for video conferencing developed by Argonne National Laboratory. It allows large distributed meetings and collaborative work sessions across the internet. Key components include vic for video conferencing, rat for audio conferencing, and additional software for shared slide presentations, chat rooms, and coordinating connections between nodes.
This document discusses Tippett Studio's use of Python to develop a new visual effects and animation pipeline called JET. Tippett Studio is an Academy Award-winning visual effects company that employs over 200 artists. They developed JET to replace their outdated pipeline. JET uses Python to rapidly develop a cross-platform, modular pipeline tool with a dynamic user interface. Key aspects of JET include chunk templates that perform pipeline tasks, batch job script generation, and UI templates to customize interfaces for different artist roles. JET provides Tippett Studio with a flexible, customizable and scalable pipeline to efficiently create computer-generated imagery.
The document discusses programming media on Windows Phone, including:
- Using the camera to take photos and manipulate the video stream.
- Accessing the microphone to record audio.
- Interacting with sensors like the motion sensor.
- Playing video content and streaming video.
- Using text to speech and speech recognition in Windows Phone applications.
This document provides an overview of basic software tools for multimedia, including text editing tools like word processors, graphical tools like painting and drawing programs, sound editing tools, and tools for animation, video and digital movies. It also discusses common file formats for video, such as QuickTime and AVI, and utilities that can be useful for multimedia projects, such as screen grabbers and format converters.
The document discusses various basic software tools for multimedia, including text editing tools like word processors, graphical tools like painting and drawing programs, sound editing tools, and tools for working with animation, video, and digital movies. It also covers common file formats for video like QuickTime and AVI. Utilities that can help with multimedia include screen grabbers and format converters.
Analysis of error in image logging between subsequent frames of a streaming v...THANMAY JS
This document discusses image acquisition properties for streaming video analysis. It explains that when acquiring frames from a video stream, it is not necessary to log every frame due to resource constraints. Key properties that control frame logging are frame rate, frame grab interval, trigger type, and number of frames per trigger. The document presents experiments that vary these properties and analyze the error in logging frames between subsequent frames. The results show that higher frame rates and more frames logged result in greater errors, while decreasing both properties simultaneously reduces error. Adjusting these image acquisition properties is important for applications like machine vision to ensure accurate timing of frame capture.
IMAGE CAPTURE, PROCESSING AND TRANSFER VIA ETHERNET UNDER CONTROL OF MATLAB G...Christopher Diamantopoulos
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
2) image transfer
3) image processing
4) sensor calibration
A user-friendly MATLAB GUI, named DIPeth, facilitates the system's control.
Learn about going from 3D scans of core samples and other rock types to visualisation, analysis and model generation with Simpleware. Trials available here: http://www.simpleware.com/software/trial/
This document discusses Pixeye, a software tool that allows for rapid development, evaluation, and configuration of image processing pipelines. Pixeye provides an integrated environment for image processing, algorithm development, mass execution and configuration, image quality assessment, and camera module integration. It aims to increase productivity by standardizing development and providing a one-stop shop for tasks typically requiring separate tools. Pixeye can load, configure, and execute image processing blocks and supports integrating new custom blocks. It provides tools for image analysis, comparison, and algorithm execution and configuration.
The document discusses various video editing techniques and concepts. It covers topics like using editing software to add sound, titles, and transitions to animation productions. It also discusses digital versus analog media, specifying project settings like frame rate and aspect ratio, and the editing process which involves organizing clips, making cuts and joins, and adding transitions. The document provides information on tools for editing, compositing, and creating output for different formats.
This document proposes a multi-view object tracking system using deep learning to track objects from multiple camera views. It uses the YOLO v3 algorithm to map segmented object groups between camera views to share knowledge. A two-pass regression framework is also presented for multi-view object tracking. Key steps include preprocessing images, extracting features, detecting and tracking objects between views using blob matching, and counting objects over time by maintaining tracks. The approach aims to improve object counting accuracy by exploiting information from multiple camera views.
This document provides instructions for using IBM SmartCloud Entry+ for System X to manage virtual servers. It discusses how to use IBM SmartCloud Entry for self-service provisioning and management. It also describes how to use Tivoli Provisioning Manager for Images (TPMfI) to capture virtual machine images, deploy images to create new virtual servers, and convert a VMware virtual machine to an IBM SmartCloud Entry appliance. The goal is to automate service deployment and management in a virtual private cloud environment.
The document discusses various 3D animation and modeling workflows and file formats, including OBJ, FBX, Collada, and Alembic formats. It also covers motion capture techniques from low to high budget options as well as cleaning up motion capture data. The document then discusses the free and open source 3D software Blender and its Cycles renderer. It also mentions the Luxrender, Radeon Pro, Unity, and Unreal game engines.
The document summarizes the Alliance Access Grid, a system for internet-based video conferencing developed by Argonne National Laboratories. It allows for group-to-group communication between multiple sites simultaneously exchanging video and audio. Key components include the vic and rat software for video and audio conferencing, and additional tools for screen sharing, slide presentations, chat, and coordinating multiple conferences. The system is designed to work over internet multicast and uses open source software running on commodity hardware.
IBM's SmartCloud Orchestrator provides end-to-end automation of cloud service delivery through workload orchestration, resource orchestration, and service orchestration. It integrates with existing data center tools and processes using open standards. The Orchestrator includes content types like software bundles, virtual images, and patterns to automate multi-tier application deployments. It also allows custom orchestration operations through actions, user interfaces, and service offerings.
LightWave 3D 11 is a 3D modeling, rendering and animation software. It offers features like instancing for mass object duplication, Bullet physics engine for realistic simulations, fracture tools for breaking 3D objects, flocking tools for natural crowd behaviors, and iridescent car paint shaders for realistic materials. LightWave 11 also enhances its interchange with ZBrush for sculpting details and improves its rendering tools and user interface for faster workflows.
Matrox Design Assistant is a flowchart-based machine vision software that allows users to create vision applications without writing code. It provides an intuitive integrated development environment where applications are built by constructing a flowchart using visual tools for image processing, measurement, pattern matching, and more. The software also enables users to design a web-based operator interface. It supports a wide range of GigE and USB3 cameras and can deploy applications to Matrox vision systems and smart cameras.
Visual Studio 2008 provides tools for code editing, debugging, and building applications. It includes an integrated development environment with support for multiple programming languages like C#, VB, and C++. The IDE can be customized with a variety of settings and options. It also provides a project system to manage code components and references across one or more projects in a solution.
This document provides a summary of Amit Prabhudesai's work portfolio. It outlines his educational background and work experience in image processing and computer vision. It then describes several projects he has worked on, including human detection using Adaboost for surveillance video, optimizing a Lane Departure Warning system for a Texas Instruments DSP, developing video analytics software for retail store customer counting and queue detection, and an Automatic Fingerprint Identification System. It also lists some relevant trainings and mentorship activities.
An Instantaneous Introduction to the Alliance Access GridVideoguy
The document summarizes the Access Grid, a model for video conferencing developed by Argonne National Laboratory. It allows large distributed meetings and collaborative work sessions across the internet. Key components include vic for video conferencing, rat for audio conferencing, and additional software for shared slide presentations, chat rooms, and coordinating connections between nodes.
This document discusses Tippett Studio's use of Python to develop a new visual effects and animation pipeline called JET. Tippett Studio is an Academy Award-winning visual effects company that employs over 200 artists. They developed JET to replace their outdated pipeline. JET uses Python to rapidly develop a cross-platform, modular pipeline tool with a dynamic user interface. Key aspects of JET include chunk templates that perform pipeline tasks, batch job script generation, and UI templates to customize interfaces for different artist roles. JET provides Tippett Studio with a flexible, customizable and scalable pipeline to efficiently create computer-generated imagery.
The document discusses programming media on Windows Phone, including:
- Using the camera to take photos and manipulate the video stream.
- Accessing the microphone to record audio.
- Interacting with sensors like the motion sensor.
- Playing video content and streaming video.
- Using text to speech and speech recognition in Windows Phone applications.
This document provides an overview of basic software tools for multimedia, including text editing tools like word processors, graphical tools like painting and drawing programs, sound editing tools, and tools for animation, video and digital movies. It also discusses common file formats for video, such as QuickTime and AVI, and utilities that can be useful for multimedia projects, such as screen grabbers and format converters.
The document discusses various basic software tools for multimedia, including text editing tools like word processors, graphical tools like painting and drawing programs, sound editing tools, and tools for working with animation, video, and digital movies. It also covers common file formats for video like QuickTime and AVI. Utilities that can help with multimedia include screen grabbers and format converters.
Analysis of error in image logging between subsequent frames of a streaming v...THANMAY JS
This document discusses image acquisition properties for streaming video analysis. It explains that when acquiring frames from a video stream, it is not necessary to log every frame due to resource constraints. Key properties that control frame logging are frame rate, frame grab interval, trigger type, and number of frames per trigger. The document presents experiments that vary these properties and analyze the error in logging frames between subsequent frames. The results show that higher frame rates and more frames logged result in greater errors, while decreasing both properties simultaneously reduces error. Adjusting these image acquisition properties is important for applications like machine vision to ensure accurate timing of frame capture.
IMAGE CAPTURE, PROCESSING AND TRANSFER VIA ETHERNET UNDER CONTROL OF MATLAB G...Christopher Diamantopoulos
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
2) image transfer
3) image processing
4) sensor calibration
A user-friendly MATLAB GUI, named DIPeth, facilitates the system's control.
Learn about going from 3D scans of core samples and other rock types to visualisation, analysis and model generation with Simpleware. Trials available here: http://www.simpleware.com/software/trial/
This document discusses Pixeye, a software tool that allows for rapid development, evaluation, and configuration of image processing pipelines. Pixeye provides an integrated environment for image processing, algorithm development, mass execution and configuration, image quality assessment, and camera module integration. It aims to increase productivity by standardizing development and providing a one-stop shop for tasks typically requiring separate tools. Pixeye can load, configure, and execute image processing blocks and supports integrating new custom blocks. It provides tools for image analysis, comparison, and algorithm execution and configuration.
The document discusses various video editing techniques and concepts. It covers topics like using editing software to add sound, titles, and transitions to animation productions. It also discusses digital versus analog media, specifying project settings like frame rate and aspect ratio, and the editing process which involves organizing clips, making cuts and joins, and adding transitions. The document provides information on tools for editing, compositing, and creating output for different formats.
This document proposes a multi-view object tracking system using deep learning to track objects from multiple camera views. It uses the YOLO v3 algorithm to map segmented object groups between camera views to share knowledge. A two-pass regression framework is also presented for multi-view object tracking. Key steps include preprocessing images, extracting features, detecting and tracking objects between views using blob matching, and counting objects over time by maintaining tracks. The approach aims to improve object counting accuracy by exploiting information from multiple camera views.
This document provides instructions for using IBM SmartCloud Entry+ for System X to manage virtual servers. It discusses how to use IBM SmartCloud Entry for self-service provisioning and management. It also describes how to use Tivoli Provisioning Manager for Images (TPMfI) to capture virtual machine images, deploy images to create new virtual servers, and convert a VMware virtual machine to an IBM SmartCloud Entry appliance. The goal is to automate service deployment and management in a virtual private cloud environment.
The document discusses various 3D animation and modeling workflows and file formats, including OBJ, FBX, Collada, and Alembic formats. It also covers motion capture techniques from low to high budget options as well as cleaning up motion capture data. The document then discusses the free and open source 3D software Blender and its Cycles renderer. It also mentions the Luxrender, Radeon Pro, Unity, and Unreal game engines.
The document summarizes the Alliance Access Grid, a system for internet-based video conferencing developed by Argonne National Laboratories. It allows for group-to-group communication between multiple sites simultaneously exchanging video and audio. Key components include the vic and rat software for video and audio conferencing, and additional tools for screen sharing, slide presentations, chat, and coordinating multiple conferences. The system is designed to work over internet multicast and uses open source software running on commodity hardware.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
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.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Comparative analysis between traditional aquaponics and reconstructed aquapon...bijceesjournal
The aquaponic system of planting is a method that does not require soil usage. It is a method that only needs water, fish, lava rocks (a substitute for soil), and plants. Aquaponic systems are sustainable and environmentally friendly. Its use not only helps to plant in small spaces but also helps reduce artificial chemical use and minimizes excess water use, as aquaponics consumes 90% less water than soil-based gardening. The study applied a descriptive and experimental design to assess and compare conventional and reconstructed aquaponic methods for reproducing tomatoes. The researchers created an observation checklist to determine the significant factors of the study. The study aims to determine the significant difference between traditional aquaponics and reconstructed aquaponics systems propagating tomatoes in terms of height, weight, girth, and number of fruits. The reconstructed aquaponics system’s higher growth yield results in a much more nourished crop than the traditional aquaponics system. It is superior in its number of fruits, height, weight, and girth measurement. Moreover, the reconstructed aquaponics system is proven to eliminate all the hindrances present in the traditional aquaponics system, which are overcrowding of fish, algae growth, pest problems, contaminated water, and dead fish.
1. Image Acquisition Toolbox lets you acquire
images and video directly into MATLAB®
and Simulink® from PC-compatible imaging
hardware. You can detect hardware auto-
matically, configure hardware properties,
preview an acquisition, and acquire images
and video. With support for multiple hardware
vendors, you can use a range of imaging
devices from inexpensive Web cameras
or industrial frame grabbers to high-end
scientific cameras that meet low-light, high-
speed, and other challenging requirements.
Together, MATLAB, Image Acquisition
Toolbox, and Image Processing Toolbox
(available separately) provide a complete
environment for developing customized
imaging applications. You can acquire
images and video, visualize data, develop
processing algorithms and analysis tech-
niques, and create graphical user interfaces.
You can use Image Acquisition Toolbox
with Simulink and Video and Image
Processing Blockset (both available separately)
to simulate and model real-time embedded
imaging systems.
Acquire images and video from industry-standard hardware
Key features
■ Automatically detects image and video acquisition devices
■
Manages device configurations
■
Provides live video previewing
■ Acquires static images and continuous video
■ Enables in-the-loop image processing and analysis
■ Provides graphical user interface for working with devices
■ Supports devices for use with MATLAB and Simulink
■ Supports multiple hardware vendors
An Image Acquisition Toolbox application that acquires and analyzes images of central
synapses to monitor synaptic transmission over time. Graphical user interfaces (upper right and
lower left) enable researchers to tune acquisition and processing parameters. Image courtesy of
Polugruto, T.A., Tervo, D.G., and Svoboda, K., Howard Hughes Medical Institute/Cold Spring
Harbor Labs.
Accelerating the pace of engineering and science
Image Acquisition Toolbox 3
2. Working with
Image Acquisition Toolbox
Image Acquisition Toolbox helps you connect
to and configure your hardware, preview the
acquisition, and acquire and visualize image
data. You can use the toolbox from the Image
Acquisition Tool, the MATLAB command
line, or the From Video Device block within
Simulink. This lets you control your image
acquisition parameters and incorporate them
into M-scripts, applications built within
MATLAB, or Simulink models.
Within the toolbox, the Image Acquisition
Tool is a graphical user interface for working
with image and video acquisition devices
in MATLAB. With this tool, you can see
all hardware available on your PC, change
device settings, preview an acquisition,
control acquisition parameters, and acquire
image or video data. You can also record
data directly to an AVI file or export hard-
ware configuration settings to an M-file so
that you can incorporate them into other
MATLAB scripts.
Connecting to Hardware
Image Acquisition Toolbox automatically
detects compatible image and video
acquisition devices. The connection to your
devices is encapsulated as an object, pro-
viding an interface for configuration and
acquisition. You can create multiple connec-
tion objects for simultaneous acquisition
from as many devices as your PC and
imaging hardware support.
Configuring Hardware
The toolbox provides a consistent inter-
face across multiple hardware devices and
vendors, simplifying the configuration
process. You configure your hardware by
using the Image Acquisition Tool or by
modifying the properties of the object asso-
ciated with the hardware on the MATLAB
command line. The toolbox also supports
camera files from hardware vendors.
You can set base properties that are common
to all supported hardware. These can include
video format, resolution, region of interest
(ROI), and returned color space. You can
also set device-specific properties, such as
hue, saturation, brightness, frame rate, con-
trast, and video sync if your device supports
these properties.
Previewing the Acquisition
Image Acquisition Toolbox video preview
window helps you verify and optimize your
acquisition parameters. It instantly reflects
any adjustments that you make to acquisition
properties. The Image Acquisition Tool has
a built-in preview window, and you can add
one to any application built with MATLAB.
A typical session with the Image Acquisition
Tool. You can use this tool instead of the
MATLAB command line to set up and
acquire images and video.
3. Acquiring Image Data
Image Acquisition Toolbox can continuously
acquire image data while you are processing
the acquired data in MATLAB or Simulink.
The toolbox automatically buffers acquired
data into memory, handles memory and
buffer management, and enables acquisi-
tion from an ROI. Data can be acquired in
a wide range of data types, including signed
or unsigned 8-, 16-, and 32-bit integers and
single- or double-precision floating point.
The toolbox supports any color space pro-
vided by the image acquisition device, such as
RGB, YUV, or grayscale. Raw sensor data in a
Bayer pattern can be automatically converted
into RGB data. The toolbox supports any
frame rate and video resolution supported by
your PC and imaging hardware.
Performing Image Acquisition
in Simulink
Image Acquisition Toolbox provides a
Simulink block that captures image or video
data directly from any device supported
by the toolbox. Along with the Video and
Image Processing Blockset you can perform
simulation and verification of image or video
processing system designs with live image or
video data.
Advanced Acquisition Features
Image Acquisition Toolbox supports three
trigger types: immediate, manual, and
hardware. Hardware triggers, which are
device-specific, let you synchronize your
acquisition to an external signal.
www.mathworks.com
A scientific camera connected to a
laptop using a FireWire connection.
MATLAB interfaces with the camera
using Image Acquisition Toolbox.
A Simulink block diagram illustrating the use of the From Video
Device block (in blue, above). The left image shows a video
frame from a connected camera and the center image shows a
histogram of the red, green, and blue channels of this input.
You can log data to disk, memory, or both
simultaneously. Image Acquisition Toolbox
lets you:
Log each image frame or log frames at
specified intervals
Log data to disk as compressed or uncom-
pressed AVI streams
Extract single images from a video stream
and store them in standard formats, includ-
ing BMP, JPEG, and TIFF
For advanced sequencing of your acquisi-
tion application, you can create callback
functions that are automatically executed
whenever events occur, such as acquisition
started or stopped, trigger occurred, and a
set number of frames acquired.
•
•
•