Semantic Annotation and Retrieval of Image Collections

Semantic-Based Image Retrial in the VQ Compressed Domain using Image Annotation Statistical Models

Semiautomatic Image Retrieval Using the High Level Semantic Labels

Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. Hence, in this paper, an image retrieval system is introduced that provided two kind of qu...

Fuzzy Neighbor Voting for Automatic Image Annotation

With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper,...

Comparative Study on Automatic Image Annotation

With the detonative development of internet technologies in the web huge amount of images are available on the web. Large amount of research has been carried out on image retrieval since last few years. There is need for efficient and viable procedure to find visual information on demand. Recent research shows that there is semantic gap between low level features of image and semantic concepts ...

Content-based histopathology image retrieval using a kernel-based semantic annotation framework

Large amounts of histology images are captured and archived in pathology departments due to the ever expanding use of digital microscopy. The ability to manage and access these collections of digital images is regarded as a key component of next generation medical imaging systems. This paper addresses the problem of retrieving histopathology images from a large collection using an example image...