image segmentation is the process of distinguishing the objects from back groung...like finding a particular cell from blood
It is important to have image segmentation because it will help when processors are trying to adjust the image quality. They use this to make it a high level image.
segmentation is the process of dividing/splitting an image into it's constituent part for analysis purpose...
As a simple answer I can say: we do segmentation to separate homogeneous area. IN image processing it can be number of pixels with the same intensity in general.
image segmentation edge detection image manipulation threshold
Image Processing classify as three type. (1) Low level image processing (noise removal, image sharpening, contrast enhancement) (2) Mid level image processing (segmentation) (3) High level image processing (analysis based on output of segmentation)
Autonomous = done automatically by a software (used in robotics) Image segmentation = dividing the image into parts that can be used later to recognize relevant image features (like objects) The definition of autonomous segmentation is summing up both terms and refers to a automatic, without human intervention, segmentation of the image. It means that the segmentation algorithms auto-calibrate themselves. This may seem a simple task for a controlled indoor environment, but can also become a huge complexity in outdoor scenes where the lightning conditions are ranging from complete darkness to direct sunlight on the sensor.
1. Image acquisition 2. Image restoration/enhancement 3. Image segmentation 4. Image interpretation
image segmentation refers to clustering or grouping of homogeneous pixels into various groups while classification is next hierarchy which labell those clustered pixels as different classes..
The term human segmentation is used for the technique of seperating individuals from a crowd in images, videos and related computer based applications. Human segmentation is a special branch of image segmentation. The goal is usually to provide data which is better and easier to analyze.
Abhir H. Bhalerao has written: 'Multiresolution image segmentation'
The segmentation for whitening teeth are RGB image combination and color adjusting. Prior to this,?æ there are filtering, border extraction, dental region identification, region flooding and area adjusting.
One can sort out all the images which are crucial bu the order of their importance while telecasting.