Content Based Image Retrieval


  Content Based Image Retrieval.ppt (Size: 1.41 MB / Downloads: 34)

ABSTRCT

Images play an important role in conveying information. With the rapid development of computer technology, the amount of digital imagery data is rapidly increasing. There is an inevitable need for efficient methods that can help in searching for and retrieving the visual information that a user is interested in. The manual annotation of images is becoming more and more an infeasible process. An ever flourishing retrieval technique is content based image retrieval (CBIR), where the visual contents found in the images are exploited for representing and retrieving the images.

INTRODUCTION

Image retrieval system
An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images.
Types of image retrieval
Text based image retrieval.
Content based image retrieval
Limitations of text based image retrieval
Annotating large volume of databases is time consuming and expensive.
Subjectivity of human perception and too much responsibility on the end-user
Problem of deeper (abstract) needs like queries that cannot be described at all, but tap into the visual features of images.

LIMITATIONS OF CBIR SYSTEM

Bridging The Semantic Gap
The semantic representation of an image can be done as follows:
The image extraction process will get the low level features of images either by color, shape, textures and spatial.
These low level features can be clustered or segmented based on the similar characteristics of the visual features to form some regions representation and next to form objects representation in the images.
The regions/objects representation will be annotated with keyword by image annotation process. This annotation process can be done either manually, semi automatically or automatically.
The image then will be represented using semantics and image retrieval can be queried based on high level concept.

CONCLUSION

CBIR aims at avoiding the use of textual descriptions and instead retrieves images based on similarities in their contents (textures, colors, shapes etc.) to a user-supplied query image or user-specified image features. General visual features most widely used in content-based image retrieval are color, texture, shape, and spatial information. Color is usually represented by the color histogram, and color moment under a certain color space. Texture can be represented by Tamura feature, Gabor and Wavelet transformation. Shape can be represented by turning angles, Fourier descriptors. CBIR scheme in the DCT domain is suitable for retrieval of color JPEG images of different sizes.