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ABSTRACT
Morphological Image Processing is an important tool in the Digital Image processing, since that science can rigorously quantify many aspects of the geometrical structure of the way that agrees with the human intuition and perception.
Morphologic image processing technology is based on geometry. It emphasizes on studying geometry structure of image. We can find relationship between each part of image
When processing image with morphological theory. Accordingly we can comprehend the structural character of image in the morphological approach an image is analyzed in terms of some predetermined geometric shape known as structuring element. Morphological processing is capable of removing noise and clutter as well as the ability to edit an image based on the size and shape of the objects of interest. Morphological Image Processing is used in the place of a Linear Image Processing, because it sometimes distort the underlying geometric form of an image, but in Morphological image Processing, the information of the image is not lost.

In the Morphological Image Processing the original image can be reconstructed by using Dilation, Erosion, Opening and Closing operations for a finite no of times.

The major objective of this paper is to reconstruct the class of such finite length Morphological Image Processing tool in a suitable mathematical structure using Java language.
The Morphological Image Processing is implemented and successfully tested in FORENSICS: Fingerprint Enhancement and reduction of noise in finger print images

Presented by:
D ASHOK KUMAR
K NARENDRA KUMAR

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ABSTRACT:-
Morphological Image Processing is an important tool in the Digital Image processing, since that science can rigorously quantify many aspects of the geometrical structure of the way that agrees with the human intuition and perception.
Morphologic image processing technology is based on geometry. It emphasizes on studying geometry structure of image. We can find relationship between each part of image. When processing image with morphological theory. Accordingly we can comprehend the structural character of image in the morphological approach an image is analyzed in terms of some predetermined geometric shape known as structuring element.
Morphological processing is capable of removing noise and clutter as well as the ability to edit an image based on the size and shape of the objects of interest. Morphological Image Processing is used in the place of a Linear Image Processing, because it sometimes distort the underlying geometric form of an image, but in Morphological image Processing, the information of the image is not lost.
In the Morphological Image Processing the original image can be reconstructed by using Dilation, Erosion, Opening and Closing operations for a finite no of times.
The major objective of this paper is to reconstruct the class of such finite length Morphological Image Processing tool in a suitable mathematical structure using Java language.
The Morphological Image Processing is implemented and successfully tested in FORENSICS:
Fingerprint Enhancement and reduction of noise in finger print images
INTRODUCTION:-
The Morphological image processing is generally based on the analysis of a two valued image in terms of certain predetermined geometric shape known as structuring element. The term morphology refers to the branch of biology that deals with the form and structure of animals and plants.
A very well suited approach for extracting significant features from images that are useful in the representation and description of region shapes is morphological (shape-based) processing. Morphological processing refers to certain operations where an object is Hit or Fit with structuring elements and thereby reduced to a more revealing shape. These structuring elements are shape primitives which are developed to represent some aspect of the information or the noise. By applying these structuring elements to the data using different algebraic combinations, one performs morphological transformations on the data.
The Morphological Image Processing operations are applied for binary images in
 FORENSICS: Fingerprint Enhancement and reduction of noise in finger print images.
DIGITAL IMAGE PROCESSING:-
Digital image processing involves the manipulation and interpretation of digital images with the aid of a computer and it is an extremely broad subject and it often involves procedures, which can be mathematically complex.
The central idea behind is quite simple. The digital image is fed in to the computer one pixel at a time. The computer is programmed to insert the data in to an equation or series of equations, and then store the results that may display or further processed. Digital image processing used to solve a variety of problems. Although often unrelated, these problems commonly require methods capable of enhancing pictorial information for human interpretation and analysis.
Employment of fingerprints as evidence of crime has been one of the most important utilities in forensics since the date 19th century. Where there are no witness to a certain crime, finger prints can be very useful in determining the offenders.
The impressions left on the surface are called latent fingerprints, and caused by the ridges on the skin. In most cases, they are incomplete and degraded. The individual features that uniquely identify a fingerprint are called minutiae. Thus, the basic ridge pattern together with the minutiae and their location on the finger print pattern uniquely identify a fingerprint. The Morphological Image Processing will enhance the degraded noisy and / or incomplete latent fingerprints.
Image enhancement and restoration procedures are used to process degraded images of unrecoverable objects or experimental results too expensive to duplicate. In physics and related fields, computer techniques routinely enhance images of experiments in areas such as high-energy plasmas and electron microscopy. Similarly successful applications of image processing concepts can be found
in astronomy, biology, nuclear medicine,
law enforcement, and defense.

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