A Study Of Image Segmentation Algorithms For Different Types Of Images
In computer vision, segmentation refers to the process
of partitioning a digital image into multiple segments
(sets of pixels, also known as superpixels).Image
segmentation is typically used to locate objects and
boundaries (lines, curves, etc.) in images. More
precisely, image segmentation is the process of
assigning a label to every pixel in an image such that
pixels with the same label share certain visual
characteristics.The result of image segmentation is a
set of segments that collectively cover the entire
image, or a set of contours extracted from the image
(see edge detection). Each of the pixels in a region are
similar with respect to some characteristic or
computed property, such as color, intensity, or
texture.Due to the importance of image segmentation a
number of algorithms have been proposed but based
on the image that is inputted the algorithm should be
chosen to get the best results. In this paper the author
gives a study of the various algorithms that are
available for color images,text and gray scale images.
Keywords: image segmentation, region growing,
marker
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