TAG BASED IMAGE RETRIEVAL (TBIR) USING AUTOMATIC IMAGE ANNOTATION

Karthikram, Mailaivasan, Parthiban, Ganesh

Abstract: In recent days, several social networking sites are more popular with digitized images. It comprises the major portion of the databases which makes the search engines to face difficulty in searching. We present a proficient image retrieval technique, which achieves eminent retrieval efficiency. Most of the images are annotated manually, thus the visual content and tags may be mismatched. This leads to poor performance in Tag Based Image Retrieval (TBIR). Automatic Image Annotation (AIA) analyzes the missing and noisy tags and over-refines it to increase the performance of TBIR. AIA can be achieved using the Tag Completion algorithm. The images retrieved from the TBIR are ranked based on the relevancy of the tags and visual content of the images. The relevancy can be evaluated using Content Based Image Retrieval (CBIR) technique. Based on the ranks, the images are indexed in the Tag matrix. Thus the images that match the search query can be retrieved in an optimal way.

Keywords: Image Retrieval, Automatic Image Annotation, Tag Based Image Retrieval (TBIR), Tag Completion Algorithm, Content Based Image Retrieval (CBIR), Tag Matrix

DOI: https://doi.org/10.15623/ijret.2014.0303027