Detection and Reconstruction of An Implicit Boundary Surface by Adaptively Expanding A

Small Surface Patch in A 3D Image

Abstract:

A conventional inverse synthetic aperture radar image is a 2-D range-

Doppler projection of a target and does not provide 3-D information. Users only

need to specify a small boundary surface patch in a 2D section image. In this

paper we are detecting the edges line extraction using the transform is to

accumulate pixels of the image in the parameter space. The detection of lines in an

image is an important task manifold distance and proposed difference of convex

functions (DC), SHT can detect almost straight lines in the image. The well-known

Improved Hough Transform and Progressive Probabilistic Hough Transform are

two of the most efficient algorithms for line detection. A recognition technique is

used to distinguish true boundary surface patches from the false ones in different

cubes. By integrating these different approaches, a high-resolution CIBS model

can be automatically reconstructed by adaptively expanding the small boundary

surface patch in the 3D image. Our method works on edge images obtained by

applying the canny edge detector to the source image. The object in the edge image

is then extracted based on the Improved Hough Transform and related conditions

of the given objects. An adaptive detection technique is applied to detect boundary

surface patches from different local regions. The technique is based on both

context dependence and adaptive contrast detection as in the human vision system.

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GLOBALSOFT TECHNOLOGIESIEEE PROJECTS & SOFTWARE DEVELOPMENTS

IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE

BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS

CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401

Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com

Our method is easy to use, which provides a valuable tool for 3D image

visualization and analysis as needed in many applications.

Existing System:

1) The problem of intensity of gradient pixel, when reconstruct a 2D

image to 3D image is an ill-possed problem.

2) In this method we produce reconstruction of objects belonging to a

variety of classes, which are restricted to classification of highly

similar shapes.

3) Based on the shape (Boundary), edge; we cannot easily able to

calculate the Points, this approach can be extended to handle other

vision related problems.

4) In this particular we have to combine line segmentation with the

reconstruction.

Disadvantages:

1) High resolutions in the directions of line segments can not always

guarantee a distinction between two straight lines.

2) The distance between two straight line segments which is not defined

easily?

3) The Length of the Straight line cannot be defined accurately.

Proposed System:

1) The reconstruction of images from 2D image to the 3D image with

the help of some efficient techniques

2) The Improved Hough transform has been the most popular

algorithm for extracting such as straight lines, segment, edge etc.,

from image global features.

3) Accumulating all pixels in the image to the Hough space, the lines

are selected only if their values at the corresponding cells are

greater than a certain threshold.

4) To detect line segments accurately this extended transform is

mainly based on the robust features of the SHT in basis of

Improved Hough Transform.

Advantages:

1) High resolutions in the directions of line segments can always

Guarantee a distinction between two straight lines.

2) The Length of the Straight line can be defined accurately.

3) The edges at the corners will be identified using the efficeient

techniques.

Software Requirements:

Platform : JAVA(JDK 1.5)

Front End : JAVA Swing

IDE : Net Beans 6.9

Operating System : Microsoft Windows XP

Hardware Requirements:

Processor : Pentium IV Processor

RAM : 512 MB

Hard Disk : 10GB

Monitor : 14” VGA COLOR MONITOR