Text recognition in scene image and video frames is difficult because of low resolution, blur, background noise, etc. Since traditional OCRs do not perform well in such images, information retrieval using keywords could be an alternative way to index/retrieve such text information. Date is a useful piece of information which has various applications including date-wise videos/scene searching, i...

In this paper we report results of experiments conducted with strategies for improving text-based image retrieval. The adopted strategies were evaluated in the photographic retrieval task at ImageCLEF2007. We propose a Webbased method for expanding textual queries with related terms. This technique was the top-ranked query expansion method among those proposed by other ImageCLEF2007 participant...

Most multimedia retrieval services e.g. YouTube, Flickr, Google etc. rely on users searching using textual queries or examples. However, this solution is inadequate when there is no text, very little text, the text is in a foreign language or the user cannot form textual a query. In order to overcome these shortcomings we have developed an image retrieval system called COPE (COnversational Pict...

Content-based image retrieval (CBIR) has been an active research topic in the last decade. In this paper we proposed an image retrieval method using global and local features. Firstly, for local features extraction, SURF algorithm produces a set of interest points for each image and a set of 64-dimensional descriptors for each interest points and then to use Bag of Visual Words model, a cluster...

In this paper, we address a ranking problem in web image retrieval. Due to the growing availability of web images, comprehensive retrieval of web images has been expected. Conventional systems for web image retrieval are based on keywordbased retrieval. However, we often find undesirable retrieval results from the keyword based web image retrieval system since the system uses the limited and in...

Content Based Image Retrieval (CBIR) is the retrieval of imagery from a collection by means of internal feature measures of the information content of the images. In CBIR systems, text media is usually used only to retrieve exemplar images for further searching by image feature content. This paper describes a new method for integrating multimedia text and image content features to increase the ...

Satellite images play an important role for collection of geographical information. However, the use of such images is limited to a greater extent due to its retrieval complexities. Traditional methods using text have also failed to yield desired and time-saving results. Therefore, Content based image retrieval using high semantic features has been developed to overcome problems related to text...

In this paper, we propose an integrated approach for medical image retrieval. In particular, we present a series of experiments in medical image retrieval task. There are three main goals for our participation of this task. First, we will test traditional well-known weighting models used in text retrieval domain, such as BM25, TFIDF and Language Model (LM), for context-based image retrieval. Se...

This paper presents the results of the University at Buffalo in the 2006 ImageCLEFmed task. Our approach for this task combines Content Based Image Retrieval (CBIR) and text retrieval to improve retrieval of medical images. Our results are comparable to other approaches presented in the task. Our results show that text retrieval performs well across the three different types of topics (visual, ...