7/29/2019 DIP PPT

1/15

PRESENTED BY K.Manjula V.Nandhini

III ECE IIIECE 09F61A0453 10F65A0405

7/29/2019 DIP PPT

2/15

CONTENTS IntroductionDefiniton & Types

Image Editor FeaturesImage FilteringProposed ModelExperimental ResultsApplicationsMerits & DemeritsConclusion

7/29/2019 DIP PPT

3/15

INTRODUCTIONDigital Image:A digital image is a representation of a two-

dimensional image as a finite set of digital values,called picture elements or pixels.Digital images can be created by a variety of input

devices and techniques, such as digital cameras,

scanners coordinate-measuring machines etc.They can also be synthesized from arbitrary non-image data.

7/29/2019 DIP PPT

4/15

Definition & TypesIt is the use of computer algorithms to perform imageprocessing on digital images.

It allows a much wider range of algorithms.

Digital images can be classified according to the number and nature of those samples.2-D region3-Dcase

7/29/2019 DIP PPT

5/15

Image Editor FeaturesCROPPING OF IMAGE:

Digital editors are used to crop images.Image cropping does not reduce theresolution of the area cropped.

SELECTIVE COLOUR CHANGE:

Image editors have color swappingabilities to selectively change the colorof specific items.

7/29/2019 DIP PPT

6/15

REMOVAL OF UNWANTED ELEMENTS:

Image editors can be used to removeunwanted branches using a "clone" tool.

COLOUR ADJUSTMENTS:

CHANGE COLOUR DEPTH:

using software,we can change the colordepth of images.

7/29/2019 DIP PPT

7/15

SPECIAL EFFECTS:

CONTRAST CHANGE AND BRIGHTENING:

Images may be skewed and distorted in various ways.

Scores of special effects can be applied toan image

Image editors have provisions to change thecontrast of images and brighten or darkenthe image.

7/29/2019 DIP PPT

8/15

Image Filtering

This operation allows performing image editing tasks such as imagesmoothing, sharpening, blurring, edge detection, mean removal andembossing.

DISTRIBUTED IMAGE FILTERING:

Divide the image into rectangular regions.Connect to the grid and send tasks.Recompose the filtered regions into the resulting image.

7/29/2019 DIP PPT

9/15

Proposed modelThe test-bed comprises of a Server nodeand a number of client nodes.

Since this model is flexible,..

FEATURES OF THE PROPOSED MODEL

linearFlexibility

Scalability Reliability

7/29/2019 DIP PPT

10/15

Experimental Results

The results are obtained from a distributedcomputing environment in which thereis a Server and two processing elements.

Centralised image The distributed image filtering is faster

than the centralized image filtering interms of processing time.

Distributed image

7/29/2019 DIP PPT

11/15

Applications

Science and engineeringRoboticsRemote sensingMulti scale signal analysisMedicineBiomedical imaging especially related to sensitivity of data, datamanagemen t.

7/29/2019 DIP PPT

12/15

Merits & DemeritsIt allows the use of much more complex algorithms for imageprocessingIt can avoid problems such as the buildup of noise and signal

distortion during processing.Used ingray-scale, Invert, X-Ray etc...

The initial cost can be high depending on the system used,the number of detectors purchased etcDigital imaging in dentistry is not standardized;

7/29/2019 DIP PPT

13/15

ConclusionDue to its various applications it is applied in many fields which gives better results compared to any other method

of editing or making it.

It is very important that when large volumes of dataare being processed then there is a significantimpact on filtering.

7/29/2019 DIP PPT

14/15

7/29/2019 DIP PPT

15/15