IMAGE SEGMENTATION full report

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INTRODUCTION

Image segmentation is an important technology for image processing. There are
many applications whether on synthesis of the objects or computer graphic images
require precise segmentation. With the consideration of the characteristics of each
object composing images in MPEG4, object-based segmentation cannot be ignored.
Nowadays, sports programs are among the most popular programs, and there is no
doubt that viewers’ interest is concentrated on the athletes.


LITERATURE REVIEW
There are many algorithms used for image segmentation, and some of them
segmented an image based on the object while some can segment automatically.
Nowadays, no one can point out which the optimal solution is due to different
constraints. In [1], a similarity close measure was used to classify the belonging of the
pixels, and then used region growing to get the object. Unfortunately, it required a set of
markers, and if there is an unknown image, it is hard to differentiate which part should
be segmented. Linking the area information and the color histogram were considered
for building video databases based on objects [2].



APPROACH
In our algorithms, there are some criteria. First of all, we need to be aware of the
target image which we would like to segment out. Second, the background image has
to be blurred and the color of the target image should be different to that of background
image as much as possible. Moreover, we expect the appendages of the target image
to cross over each other as least as possible.