Abstract:
In this paper, an automatic image
annotation and retrieval model is developed base
on the intensity invariant approach. The given
uncaptioned image is divided into background
and foreground images and segmented into
regions, which are classified into region types
using a variety of features. Firstly, preprocessing
stages such as gray-scale converting, noise
filtering for image enhancing is processed. After
segmentation, calculate the eigenvectors of
images and examined the associated word by
using database. The various types of images are
applied for training and testing. The top words
are described for annotated image in result.
Manual image annotation is time-consuming,
laborious and expensive; so, there has been a
large amount of research done on automatic
image annotation and retrieval technologies are
combined to improve the performance.
