Simple Illustrations to learn DIP

      I was scanning old newspapers. I was struck with flame's advertisement. Later I searched the internet and found the website. Then I went to the section Mass Media Campaign and then I clicked the mouse. After a while it displayed colourful illustrations via Flash software. It is not possible to copy. So I used all types of tricks to take a sample illustration. This happened on 25th Dec 2011.


Their Motto
Benefit from our nation-wide print campaign to demystify the financial literacy concepts through simple and colourful illustrations

My Motto
Benefit the upcoming technologist/Scientist to understand Digital Image Processing concepts through simple and colourful illustrations.

1. Simple to understand
2. Downloadable easily. (i.e. consume less file size)
3. Should have Creative Common Licence (i.e. No copyright problems)

http://flame.org.in/

Bookmarks 4

Big List of VLSI, Signal Processing, etc. Conferences, Journals, and Magazines
http://www.ece.ucdavis.edu/vcl/misc/conferences.html
COMMENT:: Journals' impact factor displayed. There are few article who questions the validity of impact factor.


The Thomson Reuters Impact Factor - Science - Thomson Reuters
http://thomsonreuters.com/products_services/science/free/essays/impact_factor/
The impact factor is a measure of the frequency with which the average article in a journal has been cited in a particular year or period.

Bookmarks 3

[1] Anthony TS Ho
Professor- University of Surrey - Guildford - Watermarking papers
http://www.surrey.ac.uk/computing/people/anthony_ts_ho/

[2] Cai, Jianfei's Homepage - image processing
http://www3.ntu.edu.sg/home/ASJFCai/

[3] Clement Chia Liang-Tien's Hub
http://cemnet.ntu.edu.sg/home/asltchia/index.htm

[4] Dimosthenis Karatzas -Document imaging
http://www.karatzas.co.uk/
Dimosthenis Karatzas Homepage

[5] Laurent Duval
http://www.laurent-duval.eu/lcd-publications.html
Laurent Duval, publications on signal and image processing and applications ; collaborators

[6] Lin Weisi - Associate Professor
http://www3.ntu.edu.sg/home/wslin/Index.htm

[7] Maria Vanrell Publications | Colour group
http://www.cat.uab.cat/~maria/Publications/Publications.php

[8] Raphaël Marée
http://www.montefiore.ulg.ac.be/~maree/

[9] Sappa, Angel - fulltext papers
http://www.cvc.uab.es/personal2.asp?id=89&sappaangel
CVC - Computer Vision Center

[10] Shi guangming'shomepage - DIP
http://see.xidian.edu.cn/faculty/gmshi/

[11] Yen-Lin Chen's Homepage
http://www.ntut.edu.tw/~ylchen/

[12] Yun Sheng's Homepage - FAcial expression PDE
http://www.cs.bath.ac.uk/~ys225/

[13] YKLee's homepage, Welcome!
http://www.csie.mcu.edu.tw/~yklee/

Bookmarks 2

[1] Intelligent Robotics and Computer Vision Group -
http://deim.urv.cat/%7Erivi/main.html
Homepage of the Intelligent Robotics and Computer Vision Group
COMMENT:: Links are very good

[2] Graphics, Vision and Speech - University of East Anglia (UEA)
http://www.uea.ac.uk/cmp/research/graphicsvisionspeech
 People use audio and visual signals to make sense of the world and to communicate within it.  Developing machines with the same (or enhanced) capabilities has ...

[3] CV Lab @ UCF
http://server.cs.ucf.edu/~vision/

[4] COVIG
http://covil.sdu.dk/

[5]  Centre for Vision, Speech and Signal Processing - Home
University of Surrey
http://www.ee.surrey.ac.uk/CVSSP/home

[6] Heinrich Hertz Institute - Overview - image processing department
http://www.hhi.fraunhofer.de/en/departments/image-processing/overview/

Bookmarks 1

[1] Digital Imaging Research Group
http://imaging.lboro.ac.uk/
DIRG is a Digital Imaging Research Group at the Loughborough University. The group is lead by Doctor Eran Edirisinghe. Loughborough University has an international reputation for excellence in teaching and research, strong links with industry, and unrivalled sporting achievement.

[2] Nonparametric Texture Synthesis
http://www.texturesynthesis.com/index.htm
Fast texture synthesis by nonparametric Markov random field modelling for synthesis of natural textures. Source code is provided, plus many free textures.

[3] Texture Synthesis -DIP - Very intereresting
http://www.cs.utah.edu/~michael/ts/


[4] Machine Intelligence Lab & Networking Research Group
http://mil.engr.utk.edu/nmil

[5] Computer Vision and Machine Intelligence Lab
- Aalborg Universitet (AAU)
http://469574.g.portal.aau.dk/

[6] utah - scientific computing and imaging institute
http://www.sci.utah.edu/home.html
The SCI Institute develops new methods for scientific computing, visualization and simulation as well as software for biomedical applications and a wide range of scientific research.


[7] Machine Vision Laboratory, Bristol Institute of Technology, UWE Bristol
http://www.uwe.ac.uk/cems/research/groups/mvl/projects/stoneinspection.shtml
COMMENT:: Very interesting applications Please go projects side

[8] Semiconductors and Electronic Components
http://www.visionlighttech.com/default/semiconductors
• is the first and foremost Photonics specialist for Imaging Applications
• is focusing on Partnerships with World Market Leaders
• is an Independent Advisor
• offers Top Quality Products
• is AIA Member
• is EMVA Member

[9] visionlighttech.com - Railway track inspection
http://www.visionlighttech.com/startpagina/

[10] Particle Size Analysis and Particle Shape Analysis by Sympatec
http://www.sympatec.com/index.html
Sympatec System Particle Technology manufactures instrumentation for particle size analysis and particle shape analysis for laboratory and process control.

TIFAC CORE for DIP

          The TIFAC CORE in Digital Image Processing (DIP) at M.S. Ramaiah School of Advanced studies was established in April 2003 and     completed its phase on 31st March 2006. During first phase TIFAC contributed Rs. 144 lakhs and matching contribution came from     its partner industry Valdel Corporation and the School. The second phase formally started on April 2006. The second stage total expenditure is estimated to be Rs. 452 lakhs, out of which      the Industry contribution is Rs. 115 lakhs and the matching amount is from TIFAC.

Coordinator and Contact Details

Dr. S.R. Shankapal
Coordinator - TIFAC CORE in DIP
M.S. Ramaiah School of Advanced Studies
#470-P, Peenya Industrial Area, Peenya IV Phase, Peenya, Banaglore-560058
Phone: +91-80-4906 5555
e-mail: president [AT] msrsas.org

Notables: 

• Software to process Images to screen and identify diabetic retinopathy – Arvind Eye Hospital, Madurai.

http://www.msrsas.org/relevance&interactions/tifac_dip.php

Where Computer Vision fails

The invisible Liu Bolin

Dubbed the Invisible Man, Liu Bolin of Shandong, China has created an art form of camouflage. The 38-year-old artist takes elaborately conceived photographs of himself blending in barely noticeable against his surroundings. Standing motionless for hours as he is painted over, Liu becomes a part of his backdrop, which includes everything from telephone booths to earthquake rubble. Authorities shut down Liu’s art studio in 2005 and since, “Hiding in the City”, as his series is called, is purportedly Liu’s continuing protest against the state’s crackdown on art and free expression. Enjoy these fabulous photographs, and see if you can spot the artist in them.

A woman laughes as she pushes a trolley past artist Liu Bolin during his demonstration to blend in with the vegetables on the shelves at a supermarket in Beijing, November 10, 2011. Liu, also known as the 'Vanishing Artist', started his optical illusion artworks of becoming 'invisible' more than six years ago. Picture taken November 10, 2011. REUTERS/China Daily


http://in.news.yahoo.com/photos/liu-bolin-s-disapearing-act-slideshow/#crsl=

TIFAC-CORE for Machine Vision

TIFAC -CORE

     Mission REACH (Relevance & Excellence in ACHieving new heights in educational institutions) programme has been launched in the year 2000, as a Technology Vision 2020 for India initiative, by Technology Information, Forecasting and Assessment Council (TIFAC), an autonomous organization of the Department of Science & Technology. Under the Mission, TIFAC establishes COREs (Centres of Relevance & Excellence) in Educational Institutions in diverse fields of emerging Science and Technology.

     Rajalaskhmi Engineering College (REC), Chennai has been selected for the establishment of CORE in the area of “MACHINE VISION”. The CORE has been launched and is active since 14th February 2009.

    The CORE will focus on the study of machine vision methods and techniques whereby artificial vision systems can be constructed and gainfully employed in practical applications. A common application of machine vision is the inspection of manufacturing goods for quality control as this requires high-speed, high magnification, 24/7 operation with repeatibilty of measurements.

CONTACT ADDRESS

Mrs. L. Priya, M.Tech
Training Coordinator,
TIFAC-CORE: Machine vision
Rajalakshmi Engineering College,
Thandalam,
Chennai -602105

Email: priya.l  AT rajalakshmi.edu.in

List of Clients Projects Under progress:

• Sundaram Brake Linings
• Hwashine Automotive
• Autotech Industries
• Lucas TVS
• Mando India Limited
• Accurate Products
• Auro Labs, Madurai
• Simpson & co
• Hi-Temp furnace, Pune

http://tifac-core.rajalakshmi.org/

Video Surveillance IP Camera - Texas Instruments

Texas Instruments offers multiple highly optimized reference designs based on the TMS320DM8127, DM3xx and DMVA1 DaVinci™ video processors for the IP camera market to enable developers to speed through the design process as well as reducing overall bill of materials costs.

These reference designs:

    * Reduce development time by 90%
    * Deliver higher quality video, up to 10 megapixel at reduced frame rate
    * Optimize electronic bill of materials
    * Empower customers to design sub $100 HD IP camera


DM8127 IP Camera
Part number:     TMDSIPCAM8127J3

• Description:     Single platform solution provides SVC(Scalable Video Coding) /H.264 4 megapixel 30 fps + SVC/H.264 D1 30 fps and up to 10 megapixels at reduced frame rate along with 750MHz DSP for video analytics
• Processor:     DM8127 DaVinci video processor includes ARM® Cortex-A8, DSP C674x, SVC/H.264/MJPEG video coprocessor, Gigabit EMAC, PCIe
• Sensor:     Aptina 10-MP A10030 sensor CMOS imager optimized for low-light performance
• Source Code:     Complete Linux-based IP camera application including free source code
• Video codecs:     Encode up to SVC or H.264 high profile Level 3.1 1080p at >60fps including MPEG-4 and MJPEG support

http://www.ti.com/apps/docs/mrktgenpage.tsp?contentId=41246&appId=79#dm812x

VIPER

Video and Image Processing Lab
Purdue University
USA


FEW FULL TEXT PAPERS in PDF FORMAT IS AVAILABLE UNDER EACH INDIVIDUAL PROJECTS

Research Activities as on 24-DEC-2011

Current Projects

• Analysis of Microscopy Image Sequences Collected in Living Animals
• Distributed Video Coding
• Gang Graffiti Automatic Recognition and Interpretation (GARI)
• Mobile Emergency Response Guidebook (MERGE)
• Image-Based Crack Detection System
• Purdue Sensor and Printer Forensics
• Technology Assisted Dietary Assessment (TADA)
• Video Coding
• Visual Surveillance (Advanced version of video surveillance)

Old Projects

• Texture-Based Video Coding
• Navy Smartship Project
• Multimedia Streaming
• Rate Scalable Color Image Coding
• Rate Scalable Video Coding
• Low Bit Rate Video Coding
• Real-Time Error Concealment using Texas Instruments Digital Signal Processors
• Multimedia Security: Digital Watermarking
• Analysis of Mammograms
• ATM Cell Loss Concealment
• Scalable Video Compression
• Parallel Video Compression
• Video Parsing
• Multiresolution Edge Detection
• Radar Image Processing (SAR)
• Real-Time Video Processing with the TI TMS320C80 Multiprocessor

Real-Time Video Processing with the TI TMS320C80 Multiprocessor

The TMS320C80 is Texas Instruments' single-chip multiprocessor digital signal processor (DSP) device, which contains five fully programmable processors: a master processor (MP) and four parallel processors (PPs). Performance of these processors is improved by incorporating advanced features to accelerate operation on a variety of data types.

They are investigating the use of the C80 for real-time video and image processing. In particular, They are examining how the C80 can be used for real-time video compression and video indexing.


http://cobweb.ecn.purdue.edu/~ips/

Avideh Zakhor's Home Page

University of California,
Berkeley,
USA.

Research Project (FULL TEXT PDF ARE AVAILABLE TO DOWNLOAD)

3D  Image Processing and Computer Vision

·        3D Modeling of Building Interiors
·         4D Scene Modeling and Reconstruction of Moving Objects
·       Airborne and Terrestrial 3D, Photorealistic Modeling of Urban Environment:        
·         3D Photorealistic Airborne Only Modeling;
·         Aerial Lidar Classification of Urban Landscape
·         Estimating floor-plans of buildings from the exterior;
·         Image Based Localization for Mobile Augmented Reality
 Application of Image Processing to Integrated Circuit Lithography

·       Optical Proximity Correction Algorithms
·         Layout Compression for Direct Write Lithography Systems
Multimedia Search and Retrieval 
Image and Video Compression  
 
Courses  (PPT's are available to download)

EE290T, 3D computer vision and image processing, Fall 2009 Web page
EE225b, Digital Image Processing, Spring 2007 Web page

http://www-video.eecs.berkeley.edu/~avz/

Modelling indoors

Three-dimensional models of objects, sites, buildings, structures, and urban environments made of geometry and texture are important in a variety of civilian and military applications such as training and simulation for disaster management, counteracting terrorism, virtual heritage conservation, virtual museums, historical sites documentation, mapping of hazardous sites and underground tunnels, and modeling of industrial and power plants for design verification and manipulation.
While object modeling has received a great deal of attention in recent years, 3D site modeling, particularly for indoor environments, poses significant challenges. The main objective of this proposal is to design, analyze, and develop architecture and algorithms, as well as associated statistical and mathematical framework for a human operated, portable, 3D indoor/outdoor modeling system, capable of generating photo-realistic rendering of the internal structure of multi-story buildings as well as external structure of a collection of buildings in a campus.


BEWARE
FOLLOWING LINK CONTAINS HUGE SIZE PHOTOS. SO IT EATS LOT OF BANDWIDTH

Source:: http://www-video.eecs.berkeley.edu/research/indoor/

Gang Graffiti Recognition

Gang Graffiti Recognition and Analysis Using a Mobile Telephone

Gangs are a serious threat to public safety throughout the United States. Gang members are continuously migrating from urban cities to suburban areas. They are responsible for an increasing percentage of crime and violence in many communities.

According to the National Gang Threat Assessment, approximately 1 million gang members belonging to more than 20,000 gangs were criminally active within all 50 states and the District of Columbia as of September 2008. Criminal gangs commit as much as 80 percent of the crime in many communities according to law enforcement officials throughout the nation.

Street gang graffiti is their most common way to communicate messages, including challenges, warnings or intimidation to rival gangs. It is, however, an excellent way to track gang affiliation and growth, or even sometimes to obtain membership information.

The goal of this project is to use the knowledge gained from our work in mobile devices and applications and leverage it towards the development of a mobile-based system capable of image analysis. This system will provide an accurate and useful output to a user based on a database of gang graffiti images.

The image analysis includes obtaining the metadata (geoposition, date and time) and extracting relevant features (e.g., color, shape) from the gang graffiti image. The information is sent to a server and compared against the graffiti image database. The matched results are sent back to the device where the user can then review the results and provide extra inputs to refine information. Once the graffiti is completely decoded and interpreted, it is labeled and added to the database.


https://redpill.ecn.purdue.edu//~gari/web/index.html

Edward J. Delp Homepage

Purdue University
School of Electrical and Computer Engineering
Indiana
USA

http://cobweb.ecn.purdue.edu/~ace/


Research Interests of Edward J Delp is

• Image and Video Compression
• Image Processing
• Computer Vision

Research Lab Video and Image Processing Laboratory (VIPER)


Examples of Current Research Projects Include:

1. Purdue Sensor and Printer Forensics (PSAPF)
2. The TADA Project
3. Mobile Emergency Response GuidE (MERGE)
4. Visual Surveillance
5. Automatic Recognition and Interpretation of Gang Graffiti

Printer Identification

    Techniques are available  to secure documents such as bank notes using paper watermarks, security fibers, holograms, or special inks. The problem is that the use of these security techniques can be cost prohibitive. Most of these techniques either require special equipment to embed the security features, or are simply too expensive for an average consumer. Additionally, there are a number of applications in which it is desirable to be able to identify the technology, manufacturer, model, or even specific unit that was used to print
a given document.
 
    The print quality defect known as banding in electrophotographic (EP ie LASER) printers helps  to identify the model and manufacturer of the printer. Generally different printers have different sets of banding frequencies which are dependent upon brand and model. Using this banding frequencies printers are identified. In forensics if they are able to find the printer details then from that they can trace the dealer and retailer. This in will lead them to find the criminal they are lookin for.

Paper Title :: High-Capacity Data Hiding in Text Documents,
Authors:: Aravind K. Mikkilineni,George T. C. Chiu , Jan P. Allebach , Edward J. Delp


Source :: Purdue Sensor and Printer Forensics (PSAPF)

The goals of their work are to securely print and trace documents on low cost consumer printers such as inkjet and electrophotographic (laser) printers.

http://cobweb.ecn.purdue.edu/~prints/

IJEST

International Journal of Engineering Science and Technology

Frequency: 12 issues per year
ISSN: 0975–5462 (online version);
Published by: Engg Journals Publications

IJEST is indexed in DOAJ, Google Scholar, CiteseerX, getCITED, Index Copernicus and more.

IMAGE PROCESSING  related Research and Review articles are Welcome

http://www.ijest.info/ 

Video Surveillance Book

Book Name:: Video Surveillance

Edited by: Weiyao Lin

ISBN 978-953-307-436-8, Hard cover, 486 pages
Publisher: InTech
Publication date: February 2011


This book presents the latest achievements and developments in the field of video surveillance. The chapters selected for this book comprise a cross-section of topics that reflect a variety of perspectives and disciplinary backgrounds. Besides the introduction of new achievements in video surveillance, this book also presents some good overviews of the state-of-the-art technologies as well as some interesting advanced topics related to video surveillance.


FREE TO DOWNLOAD - CREATIVE COMMON LICENSED (So no piracy problem)
PDF file size 45MB individual chapters can also be downloaded

Table of Contents Chapterwise

1. Information Management and Video Analytics: the Future of Intelligent Video Surveillance   
2. Efficient Video Surveillance: Performance Evaluation in Distributed Video Surveillance Systems
3. Federalism, Privacy Rights, and Intergovernmental Management of Surveillance: Legal and Policy Issues
4. Video Surveillance of Today: Compressed Domain Object Detection, ONVIF Web Services Based System Component Communication and Standardized Data Storage and Export using VSAF – a Walkthrough
5. Realizing Video-Surveillance on Wireless Mesh Networks: Implementation Issues and Performance Evaluation
6. An Application of Quantum Networks for Secure Video Surveillance Cooperative Visual Surveillance Network with Embedded Content Analysis Engine
7. SuperVision: Video Content Analysis Engine for Videosurveillance Applications
8. Multi-Stage Video Analysis Framework
9. Background Subtraction and Lane Occupancy Analysis
10. Block Matching-Based Background Generation and Non-Rigid Shape Tracking for Video Surveillance
11. Integrating Color and Gradient into Real-Time Curve Tracking and Feature Extraction for Video Surveillance
12. Targets Tracking in the Crowd
13. Estimation of Human Traffic Flow Using Feature-based Regression in the Spatiotemporal Domain
14. The Management of a Multicamera Tracking System for Videosurveillance by Using an Agent Based Approach
15. A Survey on Behavior Analysis in Video Surveillance Applications
16. Automatic Detection of Unexpected Events in Dense Areas for Videosurveillance Application
17. Automatic Scenario Recognition for Visual-Surveillance by Combining Probabilistic Graphical Approaches
18. A Parallel Non-Linear Surveillance Video Synopsis System with Operator Eye-Gaze Input
19. Video Surveillance for Fall Detection
20. Uncertainty Control for Reliable Video Understanding on Complex Environments
21. Hot Topics in Video Fire Surveillance
22. Animal Eyes and Video Surveillance
23. Camera Placement for Surveillance Applications
24. Real-time Stereo Disparity Map for Continuous Distance Sensing Applications - A Method of Sparse Correspondence

Source: http://www.intechopen.com/books/show/title/video-surveillance

IP Video Market Info

http://ipvideomarket.info


IP Video Market Info website claim they are the  world's leading resource on video surveillance, providing news, reviews and test results on IP cameras, DVRs, NVRs, video analytics and more.

Independent and dedicated to objective information, they say they do not accept advertising, sponsorship nor consulting projects from manufacturers.

It was launched in 2008 and they have 40000 visitors per month.


The following types questions are raised and answered to their members.

Which Megapixel cameras offer the best low light performance?

...

WDR Megapixel Camera Shootout

Dealing with direct sunlight is one of video surveillance's toughest problems.It creates both dark and bright areas, due to this image quality can suffer dramatically. Avoiding the sun is frequently impossible.

Camera's ability to handle these conditions is called WDR or Wide Dynamic Range. In this context, range refers to the variations of light levels that a camera can capture. The greater the range, the more likely the camera can handle both very bright and dark areas (e.g., sunlight on a person's face, shadow on the car in the corner).

Earlier this year, they have  did our their WDR shootout with (2) SD and (2) MP cameras. One of the clear, yet surprising, results was that cameras with more pixels (i.e., megapixel) tended to outperform (i.e., capture more image details) than standard resolution cameras, even if the SD cameras were marketed as supporting WDR.

Given those results, in this test, they wanted to learn more about the differences in megapixel camera WDR performance. To do so,they tested 6 Megapixel cameras from Arecont Vision (AV1315), Axis (P1344), Panasonic (WV-SP306 and WV-NP502), Sony (CH140) and Vivotek (IP8151P) to see who was the best and worst at handling WDR scenes.

VMS or NVR

Video Management Software OR  Network Video Recorder

 Network Video Recorder


Benefit: No staging or installation hassle

When sourcing a complete NVR solution the software is pre installed, eliminating an obstacle to successful deployment.  This mean less time at the installation site and a lower potential for problems and time consuming troubleshooting.


Benefit:  Single point of support/easier vendor management

One of the benefits of an NVR is that the hardware and software come from a single vendor.  This makes the management of vendors simpler. This also eliminates the proverbial 'finger pointing' between vendors when a problem occurs.

Benefit:  Easier to specify hardware for a particular camera configuration

One of the major design challenges is how to specify the correct server hardware for the video recording needs.  Some camera and recording configuration factors influence server processing requirements, such as:


    * Number of cameras
    * Recording frame rate
    * Live viewing frame rate
    * Compression type (MJPEG / MPEG4 / H.264)
    * Resolution of recorded/live video
    * Processing of the video (motion detection / Analytics)


Other factors influence storage required:


    * Amount of video being recorded at a given time (throughput of the disk system)
    * Resolution
    * Frame rate recorded
    * Retention time
    * Compression type
    * Scene complexity (amount of movement & variation of colors)


 Video Management System

Benefit:  Hardware flexibility

When sourcing a recording server hardware platform from a single vendor, the choices are limited to the vendor’s offerings. 

Benefit:  Compliance with organization’s standard PC vendor

Source : http://www.salientsys.com/blog/vms-or-nvr/

Arecont Vision - Company

Manufacturer of Video Surveillance Camera


Arecont was started around the year 2004 in Southern California, USA. Arecont Vision maintains leadership in megapixel imaging technologies and products. With the industry’s most comprehensive line of H.264 megapixel cameras, Arecont Vision delivers superior HD megapixel image resolution and sensitivity for mainstream video surveillance applications as well as business solutions such as operations, monitoring, control, and merchandizing.

Arecont Vision’s products leverage its patented image processing technology which provides scalable high performance megapixel imaging at a low cost. The MegaVideo® and MegaDome™ series consist of 1.3, 2, 3, 5 and 10 Megapixel H.264 and MJPEG single and dual sensor camera solutions. The SurroundVideo® series is comprised of 8 megapixel H.264 and MJPEG camera solutions with 180 degree and 360 degree panoramic configurations.


Source: http://www.arecontvision.com/

Anurag Mittal Homepage

Indian Institute of Technology,
Chennai, India
http://www.cse.iitm.ac.in/~amittal/

His research interests are in all areas of Computer Vision, with special interest in multi-camera vision systems. His thesis was on surveillance under severe occlusions using multiple cameras.

Pixelization

Source:
Lecture Notes: Pixelization and Quantization
Richard Alan Peters II,
EECE\CS 253 Image Processing

Shahram Ebadollahi Homepage

Columbia University
Newyork City,
USA

http://www.ee.columbia.edu/~shahram/main.html


Most of the sections of his site is under construction.
In his lecture notes I read about "Morphological Operations"

Lecture Notes
 Course code - ELEN E4830 
 Year        - Spring 2009
 Course Name - Digital Image Processing
                http://www.ee.columbia.edu/~xlx/ee4830/outline.html

Richard Alan Peters Homepage

Vanderbilt School of Engineering,
Nashville, Tennessee,

USA.

http://www.vuse.vanderbilt.edu/~rap2/AlsMainPage.html

Lecture notes is very good. It can be downloaded for free.
http://www.archive.org/details/Lectures_on_Image_Processing

Video Surveillance

A CCTV (or closed-circuit television) camera is an analog video camera that transmits signals via coaxial cable to a single central location for monitoring, recording, and video analysis. While the recent trend is a push towards IP network cameras, CCTV cameras are still widely used, and offer a cost-effective answer to many common surveillance scenarios.

CCTV technology has been around since the 1940's, and became a major player in the security industry around 1970. The two main

      PROS and CONS

•    Lower initial cost
•    Wide-spread compatibility
•    Expensive cabling - ( For large-scale surveillance applications)
•    Limited features

Components of a CCTV System

    * Cameras
    * Monitor
    * Cable

CCTV Camera Types

• Fixed  CCTV cameras point in a single direction, which makes them perfect for monitoring very specific areas of interest. These  cameras are quite effective not only for capturing footage of suspicious activity, but also for deterring criminals and vandals from carrying out their acts in the first place. 
• PTZ cameras are ideal for wide-area surveillance. They give operators the ability to remotely control pan, tilt, and zoom functions to follow activity and to zoom in for detailed monitoring.

Most standard CCTV cameras offer a TVL (Television Lines) resolution of around 380, while high-resolution cameras will deliver something closer to 540 TVL

IP-based video surveillance has improved the effectiveness of video security by leaps and bounds over the analog CCTV equipment we've grown so accustomed to over the years.

    * Simple cabling system
    * Connected to Internet
    * Scalability
    * Simpler storage (Stored in video servers)


Along with streaming video footage, network cameras can include a number of additional functionalities, such as pan/tilt/zoom operation, motion detection, audio surveillance, integration with alarms and other security systems, automated alerts, intelligent video analytics, and much more. Many IP cameras can also send multiple streams of video, using different compression technologies for live viewing and archiving.

Source: Videosurveillance.com

http://www.videosurveillance.com/

VideoSurveillance.com is  an online retailer started in 2008 specialized in video surveillance equipments.

Intelligent headlights Control

ADVANCED DRIVER ASSISTANCE SYSTEMS
Computer Vision Center
Universitat Autònoma de Barcelona,
Spain.

This systems pretend to automatically regulate the headlights' beam angle to illuminate as much of the road ahead as possible, without dazzling other drivers. The classifier is a very important element. It is able to distinguish rear-lights and blobs due to vehicles' head from those originating from road lamps and reflective elements like poles and traffic signs.

Intelligent Recognition & Digital Security Group

National Laboratory of Pattern Recognition
Institute of Automation Chinese Academy of Sciences,
Beijing,CHINA.

http://nlpr-web.ia.ac.cn/english/irds/index.html


The Intelligent Recognition & Digital Security Group, formed in 1998 by Prof. Tieniu Tan, is subordinated to NLPR (National Laboratory of Pattern Recognition).  The group  interests in computer vision and pattern recognition, especially in the following domains:
1. Intelligent visual computing
2. Intelligent video surveillance

     Security has become a major world-wild concern since the event of September 11, 2001 in USA and the bomb attacks in London on the July 2005. Video surveillance is a critical component of any effective security system. Most current video surveillance systems are monitored by relatively small teams of human operators even though there may be a very large number of cameras. Typically a human watches a set of screens which cycle from one camera to another every few seconds. In addition to problems of fatigue and boredom, the human attention span is limited both spatially and temporally. To overcome these limitations, Intelligent Video Surveillance system , from the computer vision and pattern recognition field, is developed for the real-time monitoring of humans and vehicles. These systems can interpret the events in the camera and generate an alarm if a suspicious person or an abnormal activity is detected.

3. Biometric acquisition and recognition
4. Cyber data understanding and security

Computation Vision - Univ. of Reading

Computational Vision
Computing Research Group,
University of Reading,
England

http://www.reading.ac.uk/sse/research/sse-computing.aspx

Top researchers

• Dr James Ferryman
• Dr Hong Wei
• Dr Oswaldo Cadenas

Research is concerned with the computational issues of perception and reasoning in relation to image interpretation. There is a present focus on automated CCTV analysis for security and threat assessment, biometrics, and segmentation and classification of remotely sensed LIght Detection And Ranging (LIDAR) data.

The University of Reading is ranked as one of the top 200 universities in the world.

Document Analysis

Document Analysis is a discipline that combines image analysis and pattern recognition techniques to process and extract information from documents from different sources. Sources include either raster formats, after scanning paper-based documents, or electronic formats such as ps, html, pdf, etc. Document Analysis consists of three major research subfields: paper layout analysis, optical character recognition and graphics recognition.

Document Analysis is a discipline that combines image analysis and pattern recognition techniques to process and extract information from documents from different sources. Sources include either raster formats, after scanning paper-based documents, or electronic formats such as ps, html, pdf, etc. Document Analysis consists of three major research subfields: paper layout analysis, optical character recognition and graphics recognition. The Document Analysis Group of the CVC has research and development experience in the following concerns: symbol recognition, indexing and browsing by graphical content, sketchy interfaces, diagrammatic reasoning and visual languages for graphic documents, graphics recognition architectures, reading systems for forms and structured documents, camera-based OCR, fingerprint recognition.


Source: Computer Vision Center

Computer Vision Center

Computer Vision Center
Universitat Autònoma de Barcelona,
Spain.


Research and Development Fields

• ADVANCED DRIVER ASSISTANCE SYSTEMS 
• COLOR IN CONTEXT
• DOCUMENT ANALYSIS
• INTERACTIVE & AUGMENTED MODELING
• MACHINE VISION
• MEDICAL IMAGING
• OBJECT RECOGNITION
• RESEARCH LAB ON IMAGE SEQUENCE EVALUATION
• ROBOT VISION

Yue M.Lu Homepage

Yue M. Lu
Assistant Professor of Electrical Engineering
Harvard School of Engineering and Applied Sciences


http://lu.seas.harvard.edu/publications.html

Tapas Kanungo Homepage

http://www.kanungo.com/

• Optical Character Recognition (OCR) Page

Xavier Baro HomePage

Xavier Baro
Universitat Oberta de Catalunya (UOC)
Barcelona, Spain.
http://xbaro.wordpress.com/



A new book on “Traffic Sign Recognition Systems” has been published. http://dx.doi.org/10.1007/978-1-4471-2245-6

Research
In 2003 he joined to the Computer Vision Center. His research interests are related to machine learning, evolutionary computation, and statistical pattern recognition.

A. Murat Tekalp's Homepage

A. Murat Tekalp 
University of Rochester, 
New York,USA
http://home.ku.edu.tr/~mtekalp/

Author of following book:
Digital Video Processing, 1/e
Published August, 1995 by Prentice Hall PTR (ECS Professional)
560 pp.   ISBN 0-13-190075-7
$78.00