In this paper, we study the problem of image-text matching. Inferring the latent semantic alignment between objects or other salient stuffs (e.g. snow, sky, lawn) and the corresponding words in sentences allows to capture fine-grained interplay between vision and language, and makes image-text matching more interpretable. Prior works either simply aggregate the similarity of all possible pairs ...

Hand written Character Recognition is area of research since many years. Automation of existing manual system is need of most industries as well as government areas. Recognition of hand written characters is a demand for many fields. In this paper we have discussed our approach for hand written character segmentation. This paper discusses various methodologies to segment a text based image at v...

This paper provides an overview of Kernel Canonical Correlation Analysis. KCCA is a technique for finding common semantic features between different views of data. Applications on text retrieval, categorization and image retrieval based on text queries are presented.

In this paper we proposed an approach to deal with the Chinese-English cross-language image retrieval problem. Text-based image retrieval and query translation were adopted in the experiments. A similarity-based backward transliteration model with candidate filter was proposed to translate the proper nouns. The experimental results showed that using similarity-based backward transliteration inc...

For this year’s Image CLEF Photo Retrieval task, we have prepared 5 submission runs to help us assess the effectiveness of 1) image content-based retrieval, and 2) textbased retrieval. We investigate whether the clustering of results can increase diversity by returning as many different clusters of images in the results as possible. Our image system uses the FIRE engine to extract image feature...

Humans can associate vision and language modalities and thus generate mental imagery, i.e. visual images, from linguistic input in an environment of unlimited inflowing information. Inspired by human memory, we separate a text-to-image retrieval task into two steps: 1) text-to-image conversion (generating visual queries for the 2 step) and 2) image-to-image retrieval task. This separation is ad...

In this paper, we check the limitations of image annotation on a large real corpus. We built a corpus of documents containing text and pictures, using more than 25000 press articles. We use this data to compare the similarity between a text-based retrieval and an image-based retrieval. The retrieval systems we use are common Information Retrieval (IR) tools. Results show that the two IR systems...

In this article, a fabulous method for database retrieval is proposed.  The multi-resolution modified wavelet transform for each of image is computed and the standard deviation and average are utilized as the textural features. Then, the proposed modified bit-based color histogram and edge detectors were utilized to define the high level features. A feedback-based dynamic weighting of shap...

An increasing number of clinicians, researchers, educators and patients routinely search for medical information on the Internet as well as in image archives. However, image retrieval is far less understood and developed than text–based search. The ImageCLEF medical image retrieval task is an international benchmark that enables researchers to assess and compare techniques for medical image ret...

Image representation schemes designed for image retrieval systems are categorized into two classes: Keyword (text) features and Visual features. The query scenario in image retrieval system based on keyword features (Chang and Hsu 1992 ; Shen et al 2000) is Query by Keyword (QBK). Semantics of images can be accurately represented by keywords, as long as keyword annotations are accurate and comp...