An image segmentation c++ project may be defined as two dimensional function as f(x, y) where x and y are spatial (plane) coordinates and the amplitude of f at any pair of coordinates (x, y) is called the 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. The field of digital image processing refers to processing digital images by a digital computer.
Elements are referred to as picture elements, image elements, peels and pixels. Segmentation refers to the process of partitioning a digital image into multiple regions.
The goal of segmentation is to simplify or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves) in images.
The result of Image Segmentation is a set of regions that cover the entire image or a set of contours extracted from the image. A Voxel is a volume element representing a value on a regular grid in 3-D space.
This is analogous to a pixel, which represents 2-D image data voxels are frequently used in the visualization and analysis for medical and scientific data. In 3-D space each of the co-ordinates is defined interns of its position, colour and density. Think of a cube where any point on an outer side is expressed with an x, y and the third Z co-ordinate defines a location into the cube from that side, its density and its colour with this information and 3-D rendering software, a 2-D view from various angles of an image can be obtained and viewed at our computer.
Medical Practitioners and Researchers are now using images defined by voxels and 3-D software to view X-rays cathode tube scans and Magnetic Resonance Imaging MRI) scans from different angles effectively to see the inside of the body from outside.
Objective:
The main objective of Image Segmentation is to divide an image into regions that can be considered homogeneous with respect to a given criterion such as color or texture.
Segmentation is an essential part of any Image analysis system and especimedical Medical environments where segmented images provide valuable information for Diagnosis.
Computation of 3D-GSC algorithm for real-time 3D image segmentation in medical and industrial applications.
Conclusion:
There are varieties of useful applications that demonstrate the need for precise segmentation of image data. This chapter describes the need for segmentation and types of segmentation and video segmentation.
Click Here To Download Project Report of IEEE CSE Image processing c++ Project .
