image processing project and implimentations
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04-01-2010, 05:19 PM




To get project and implimentation report and source code of specific image processing project and implimentations topic please browse through topicideaslist-of-electronics-electrical-instrumentation-applied-electronics-project and implimentation-ideas



a. IMPLEMENTATION OF BQ ALGORITHM & ARITHMETIC CODING FOR DATA COMPRESSION.
b. NOISE CLEANING USING AVERAGING, MEDIAN AND ROTATING FILTERS & CONTRAST ENHANCEMENT USING GAMMA CORRECTION OF DIGITAL TRUE COLOR IMAGES
c. IMPLEMENTATION OF EDGE DETECTION TECHNIQUES USING MATLAB
d. IMPLEMENTATION OF SPATIAL AND FREQUENCY DOMAIN TECHNIQUES FOR IMAGE ENHANCEMENT
e. IMPLEMENTATION OF HISTOGRAM EQUALIZATION TECHNIQUES
f. IMAGE COMPRESSION USING BIORTHOGONAL 3.7 WAVELET TRANSFORMS
g. IMPLEMENTAION OF IMAGE RESTORATION & IMAGE ENHANCEMENT TECHNIQUES USING MATLAB
h. IMPLEMENTATION OF ALGORITHMS FOR SUCCESSIVE INTERFERENCE CANCELLATION IN CDMA USING MATLAB
i. IMPLEMENTATION OF WCDMA USING VHDL
j. IMAGE WATERMARKING USING WAVELETS & DIRECTIONAL FILTER BANKS
k. MORPHOLOGICAL OPERATORS FOR COLOR IMAGE PROCESSING
l. THE CURVELET TRANSFORM FOR IMAGE DENOISING
m. CONTENT BASED IMAGE RETRIEVAL SYSTEM USING PCA
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26-06-2010, 10:10 PM

1.DWT based scene adaptive color quantization
2.Human identification system using iris
3.D D - wavelet transform in image compression
4.Lost pixel recovery in wavelet coding domain
5.Voting system using fingerprint
6.Performance analysis of Haar wavelet based image compression
7.Data hide and seek technique-Steg analysis
8.Implementation of jpeg standard
9.Data compression coder and decoder using transform coding
10.DCT based content security system using additive algorithm
11.Visual half toning-mini project and implimentation
12.Image water marking using wavelets
13.Finger printing-secured technique for Internet applications
14.Color to gray and back:color embedding in to texture gray images
15.Pre \ Post filtering for DCT-based block coding systems
16.Cocktail water marking for secure data hiding
17.Lossless compression for color mosaic images
18.Number plate recognition
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#3
19-03-2011, 01:20 AM

i want to take the difference of two images and displaying the change afterward ..
how can it be done ?
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#4
06-08-2011, 01:10 PM

give me resource of image processing project and implimentation
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27-01-2012, 09:57 AM


to get information about the topic morphological image processing full report,ppt and related topic please refer the link bellow

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topicideashow-to-image-processing-project and implimentations

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23-03-2012, 01:47 PM

image processing project and implimentations



.docx   image processing.docx (Size: 154.89 KB / Downloads: 27)

This article is intended as an introductory look at image processing (not machine vision). We will look at how colour is represented within an image, how images are stored, what resolution means, as well as the most rudimentary statisical analysis of an image: the histogram.

Colour Representation

A quick look at how colour is represented on a computer. The two most commonly used representations are 8-bit greyscale and 24-bit colour. 8-bit greyscale contains 256 shades of grey (28 = 256) with 0 normally denoting black and 255 denoting white, with other values representing intermediate shades of grey. 24-bit colour is simply stored as 3-bytes denoting the red, green and blue components of the colour:


It is worth mentioned that colour can be stored in a variety of other ways, each of which have their own advantages and disadvantages: HSI (Hue, Saturation, Intensity), CMY (Cyan, Magenta, Yellow), Normalized RG, CIE, YIQ and a lot more.

Image Representation
Now that we understand how colours are stored, what about whole images? Simply put, images are stored as collections of pixels ('pixel' is in fact short for 'picture element'), each of which is assigned a colour. As an example, the left wing of this Su-47 has been blown up so you can see how the individual colours interact to create the star:

How much information can you convey in an image this way? This depends on the resolution at which the image is sampled. Sampling occurs when you scan an image, or take a picture with a digital camera. As with everything digital, the information provided has to be converted into discrete information, so the scanner/digital camera samples as much information as it can and converts it into a digital signal. With digital cameras, this is represented by the size of the CCD sensor (normally measured in megapixels). The greater the number of pixels the CCD contains, the larger the resolution, the more information is sampled.



Histograms
A histogram is one of the simplest methods of analyzing an image. An image histogram maintains a count of the frequency for a given colour level. When graphed, a histogram can provide a good representation of the colour spread of the image. Histograms can also be used to equalize the image, as well as providing a large number of statistics about it. Here is an example of a histogram for the greyscale version of the Su-47 shown above:



References
Efford, Nick. Digital Image Processing: A Practical Introduction Using Java. Addison-Wesley. Essex: 2000.
1. ABSTRACT REAL TIME IMAGE PROCESSINGThe multidisciplinary field of real-time image processing has experienced a tremendousgrowth over the past decade. The purpose of real time image processing is to improvethe video quality by eliminating the noise inside the sequence. It is intended to provideguidelines and help bridge the gap between the theory and the practice of image andvideo processing by providing a broad overview of proven algorithmic, hardware,software tools and strategies.RTIP involves many aspects of hardware and software in order to achieve highresolution input,low latency capture ,high performance processing,efficient display. MacOS X offers all of the necessary features for the development of high performance RTIPapplications, although careful choice of peripherals and software techniques are required.Regarding the potential of the parallel platform for image processing, in the near futurewe will focus our attention on the improvement of the scheduling component, by usingprocessor units with different processing capacities and also other service policy for thequeue of jobs. Algorithm measuring basic queue parameters such as period of occurrencebetween queues, the length and slope of occurrence have been discussed.
2. LIST OF FIGURESFIGURE NAME PAGE NOFig 2.1 System Design 5Fig 3.1 Test Image For Line Detection 13Fig 5.1 Image Analysis System Structure 21Fig 5.2 Queue Detection 27Fig 5.3 Edge Detection 27
3. LIST OF SYMBOLSRTIP – Real Time Image ProcessiungILP-Instruction Level ParallelismDLP – Data Level ParallelismTMJ – Traffic Movement at Junction
4. LIST OF TABLESTable 2.1 Broadcast video standards 5
5. TABLE OF CONTENTSCHAPTER NO TITLE PAGENO ABSTRACT i LIST OF FIGURES ii LIST OF SYMBOLS iii LIST OF TABLE iv 1. INTRODUCTION 1 1.1 PURPOSE 1 1.2 SCOPE 1 1.3 OVERALL DESCRIPTION 1 1.4 OBJECTIVE 2 2. HARDWARE PLATFORM TO RTIP 4 2.1 INTRODUCTION 4 2.2 REAL TIME IMAGE PROCESSING 4 2.3 SAMPLING RESOLUTION 5 2.4 LOW LATENCY VIDEO INPUT 6 2.5 LOW LATENCY OPERATING SYSTEM 6 SCHEDULING 2.6 HIGH PROCESSING PERFORMANCE 7 2.7 VIDEO CAPTURE HARDWARE 7 2.8 MAC OS X 83 REAL TIME IMAGE PROCESSING ON 9 DISTRIBUTED COMPUTER SYSTEM 3.1 INTRODUCTION 9 3.2 DEFINITIONS 9 3.2.1 REAL TIME IN PERPETUAL SENCE 9 3.2.2 REAL TIME IN SOFT SENSE 10


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#7
14-05-2012, 03:34 PM

image processing project and implimentations



.ppt   tagore.ppt (Size: 698 KB / Downloads: 42)

Facial Recognition Software



Facial recognition software fall into a larger group of technologies known as biometrics.
The basic idea behind biometrics is that our bodies contain unique properties that can be used to distinguish us form others.
The basic methods of biometric are:
fingerprint scan
Retina Scan
Voice Identification



Facial recognition software can be used to find criminals in a crowd, turning a mass of people into a big line up.


Nodal Points

There are 80 nodal points on a human face. Distance between eyes Width of nose Depth of eye sockets Cheekbones Jaw line Chin


Applications n Uses


Cameras
Video cameras
Scientific cameras

Elections
Criminal investigation
Secure Personal Computer


Conclusion


I have concluded that ,In present technology, movies mainly consist of animations and graphics. Image processing plays a major role in animations.
So in the future, importance of image processing increases to a very large extent.



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16-05-2012, 01:55 PM

image processing



.doc   imageprocessing.doc (Size: 34 KB / Downloads: 29)

Definition
Every biometric system has its limitations. Therefore, identification based on multiple biometrics is an emerging trend as multimodel biometrics can provide a more balanced solution to the security multimodel systems involve the use of more than one biometric system. Our contribution to the above subject is that we have developed an algorithm on banking security. For this we have considered a bank using biometric technology for its security purpose. The security is assured by using finger scan, voice scan, hand geometry scan and by requesting the password given by the bank for a particular user when necessary.
Biometrics technology allows determination and verification of ones identity through physical characteristics. To put it simply, it turns your body in to your password. We discussed various biometric techniques like finger scan, retina scan, facial scan, hand scan etc. Two algorithms have been proposed by taking biometric techniques to authenticate an ATM account holder , enabling a secure ATM by image processing. Biometrics is now applied in various public and private sectors.

What is Digital Image Processing?

An Image may be defined as a two dimensional function f (x,y) where x and y are spatial(plane) coordinates x, y is called intensity or gray level of the image at that point. When x, y and the amplitude values of f are all finite, discrete quantities, we call the image a digital image.
Interest in digital image areas: improvement of pictorial information for human interpretation: and representation for autonomous machine perception.
The entire process of Image Processing and starting from the receiving of visual information to the giving out of description of the scene, may be divided into three major stages which are also considered as major sub areas, and are given below
(i) Discretization and representation : Converting visual information into a discrete form: suitable for computer processing: approximating visual information to save storage space as well as time requirement in subsequent processing.
(ii) Processing : Improving image quality by filtering etc ; compressing data to save storage and channel capacity during transmission.
(iii) Analysis: Extracting image features; qualifying shapes, registration and recognition.

Draw back of passwords-need for Biometrics

No more problems if forgotten passwords and id codes, biometrics is the technology taking care of it which turns your body into your password. Typically, the more rigorous you make your password selection and construction rules the more difficulty users will have in remembering their passwords. Unfortunately, strict password rules are necessary to stop simple hacker attacks on the network.
The fundamental problem with password is two fold. First, they are transferable they can be written down on paper, they can be transferred to some one who should not have them. Second, and just as important, they can be forgotten. Recent research suggests that a forgotten password can cost as much as US$ 340 per event! This is n't too surprising. Clearly, the risk and costs of compromised passwords are a significant facto to consider in developing any sure system. The critical need for additional level of security has given rise to the field of

“BIOMETRICS”
ABSTRACT


This paper encloses the information regarding the ‘IMAGE PROCESSING’. And discussed one of the major application of image processing ‘BIOMETRICS’. Biometrics technology allows determination and verification of ones identity through physical characteristics. To put it simply, it turns your body in to your password. We discussed various biometric techniques like finger scan, retina scan, facial scan, hand scan etc. Two algorithms have been proposed by taking biometric techniques to authenticate an ATM account holder , enabling a secure ATM by image processing. Biometrics is now applied in various public and private sectors. No doubt, biometrics is going to be next generation’s powerful security tool…!
What is Digital Image Processing?

An Image may be defined as a two dimensional function f (x,y) where x and y are spatial(plane) coordinates x, y is called intensity or gray level of the image at that point. When x, y and the amplitude values of f are all finite, discrete quantities, we call the image a digital image.
Interest in digital image areas: improvement of pictorial information for human interpretation: and representation for autonomous machine perception.

The entire process of Image Processing and starting from the receiving of visual information to the giving out of description of the scene, may be divided into three major stages which are also considered as major sub areas, and are given below

(i) Discretization and representation: Converting visual information into a discrete form: suitable for computer processing: approximating visual information to save storage space as well as time requirement in subsequent processing.
(ii) Processing :Improving image quality by filtering etc ; compressing data to save storage and channel capacity during transmission.
(iii) Analysis: Extracting image features; qualifying shapes, registration and recognition.
We concentrated on human interpretation application and developed two algorithms which can make the ATM secure by image processing.
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#9
13-07-2012, 03:25 PM

image processing


.pdf   image_processing.pdf (Size: 637.92 KB / Downloads: 96)

What is an image?

An image is an array, or a matrix, of square pixels (picture elements) arranged in columns and rows.
In a (8-bit) greyscale image each picture element has an assigned intensity that ranges from 0 to 255. A grey scale image is what people normally call a black and white image, but the name emphasizes that such an image will also include many shades of grey.


RGB

The RGB colour model relates very closely to the way we perceive colour with the r, g and b receptors in our retinas. RGB uses additive colour mixing and is the basic colour model used in television or any other medium that project and implimentations colour with light. It is the basic colour model used in computers and for web graphics, but it cannot be used for print production.
The secondary colours of RGB – cyan, magenta, and yellow – are formed by mixing two of the primary colours (red, green or blue) and excluding the third colour. Red and green combine to make yellow, green and blue to make cyan, and blue and red form magenta. The combination of red, green, and blue in full intensity makes white.


Gamut

The range, or gamut, of human colour perception is quite large. The two colour spaces discussed here span only a fraction of the colours we can see. Furthermore the two spaces do not have the same gamut, meaning that converting from one colour space to the other may cause problems for colours in the outer regions of the gamuts.

Astronomical images

Images of astronomical objects are usually taken with electronic detectors such as a CCD (Charge Coupled Device). Similar detectors are found in normal digital cameras. Telescope images are nearly always greyscale, but nevertheless contain some colour information. An astronomical image may be taken through a colour filter. Different detectors and telescopes also usually have different sensitivities to different colours (wavelengths).



Natural colour images

It is possible to create colour images that are close to “true-colour” if three wide band exposures exist, and if the filters are close to the r, g and b receptors in our eyes. Images that approximate what a fictitious space traveller would see if he or she actually travelled to the object are called “natural colour” images.
To make a natural colour image the order of the colours assigned to the different exposures should be in “chromatic order”, i.e. the lowest wavelength should be given a blue hue, the middle wavelength a green hue and the highest wavelength should be red.
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#10
10-10-2012, 11:45 AM

to get information about the topic "image processing" full report ppt and related topic refer the link bellow

topicideashow-to-digital-image-processing-full-report

topicideashow-to-image-processing-compression-techniques-download-full-seminar and presentation-report

topicideashow-to-image-processing-project and implimentations

topicideashow-to-image-processing-full-report

topicideashow-to-digital-image-processing-ppt

topicideashow-to-image-processing-steganography
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#11
05-11-2012, 02:15 PM

Image Processing



.docx   Image Processing.docx (Size: 20.24 KB / Downloads: 24)

Image processing is a technique to enhance raw images received from cameras/sensors placed on satellites, space probes and aircrafts or pictures taken in normal day-to-day life in various applications. Most image processing techniques involve treating the image as a two-dimensional signal and applying standard signal processing techniques to it. For example, this processing May remove noise. Improve the contrast of the image. Remove blurring caused by movement of the camera during image acquisition.

ROTATION:

Image rotation is performed by computing the inverse transformation for every destination pixel. One of the techniques of rotation is 3-pass shear rotation .

IMAGE ENHANCEMENT :

Image enhancement is the improvement of digital image quality, without knowledge about the source of degradation. To make an image lighter or darker, or to increase or decrease contrast, pseudo colouring, noise filtering, sharpening and magnifying. Programs --> image enhancements --> image editors. The aim of image enhancement is to improve the interpretability or perception of information in image. EXAMPLE : NOISE SMOOTHING. CONTRAST MANIPULATION.

IMAGE NOISE REDUCTION:

“ Noise filtering” filter the unnecessary information from an image. It is also used to remove various types of noises from the images . IMAGE RESTORATION: Image restoration removes or minimizes some known degradations in an image. Degradation comes in many forms such as motion blur, noise, and camera miss focus . It is a special kind of “ image enhancement ”. A point-spread function, called a filter, can be constructed that undoes the blurring. Inverse filtering

Applications:

Photography and printing Satellite image processing Medical image processing Face detection, feature detection, face identification Microscope image processing Car barrier detection Morphological image processing

Conclusion:

Benefits : Refined images can be obtained, faster report turnaround, easing of growing workload, etc... I mprovements : block artifact. mosquito noise reduction. adaptive contrast enhancement. sharpness and texture enhancement. selective color correction. By embracing the new image processing technologies and further refinements in image processing techniques, users are likely to find it more beneficial, not less, in future, while more refinements in image processing techniques will be appreciated at a reduced cost
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#12
10-11-2012, 01:14 PM

IMAGE PROCESSING


.doc   IMAGE PROCESSING[.doc (Size: 479.02 KB / Downloads: 21)

INTRODUCTION

Work Flow management is a fast evolving technology which is increasingly
being exploited by businesses and in a variety of industries.
Its primary characteristics is the automation of process involving
combinations of human and machine based activities, particularly those
involving interaction with IT applications and tools. Although its most
prevalent use is within the office environment in staff intensive operations
such as insurance, banking, legal and general administration, etc. it is also
applicable to some classes of industrial and manufacturing.

The Evolution of Workflow

Many types of product in the IT market have supported aspects of workflow
functionality.

Image Processing

Workflow has been closely associated with image systems and many image
systems have workflow capability either built-in or supplied in conjunction
with a specific workflow product
.
Document Management

Document management technology is concerned with managing the lifecycle
of electronic documents.

Electronic Mail and Directories

Electronic mail provides powerful facility for distributing information
between individuals within an organization or between organizations. Thus
electronic mail systems have themselves been progressing towards workflow
functionality through the proper channel.
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01-01-2013, 10:22 AM

to get information about the topic" image processing" full report ppt and related topic refer the link bellow

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#14
04-08-2013, 02:15 PM

i need a projevt based on atm security system
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16-08-2013, 09:25 PM

please provide me some information/project and implimentation ideas about 'Imaging of brain'.....
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