Now days, face image of people is the interesting area of users. Most of the time images are in digital form. Thus, content-based face image retrieval is a technique which facilitates for many emerging applications. In this paper, automatically detected human attributes are used to enhance the performance of content based face image retrieval. Here, low level features of image are combined with...

Nowadays, more and more images are available. However, to find a required image for an ordinary user is a challenging task. Large amount of researches on image retrieval have been carried out in the past two decades. Traditionally, research in this area focuses on content based image retrieval. However, recent research shows that there is a semantic gap between content based image retrieval and...

Since the use of large image databases gains in importance nowadays, efficient querying and browsing through image repositories becomes increasingly essential. Compared to text retrieval techniques there are even more problems with image retrieval. Particularly, the semantic gap between low-level visual features of images and high-level human perception of inferred semantic contents decreases t...

There is a gap between low-level descriptions of image content and the semantic understanding of users to query image databases in the content-based image retrieval. In this paper, we put forward a method of classifying image regions hierarchically using their semantics and that resembles peoples’ perception more than using low-level features. The experiments show, the better precision of seman...

We present an image retrieval system for the interactive search of photo collections using free-hand sketches depicting shape. We describe Gradient Field HOG (GF-HOG); an adapted form of the HOG descriptor suitable for sketch based image retrieval (SBIR). We incorporate GF-HOG into a Bag of Visual Words (BoVW) retrieval framework, and demonstrate how this combination may be harnessed both for r...

Due to the increase in the size of World Wide Web, content based retrieval becomes more challenging and also it provides a lot of irrelevant results. We propose a new ‘Concept and Content based Image Retrieval Technique’ to provide exact results. We use associative mining technique with the semantic concepts. Our methodology indexes the images according to semantic concepts and generates associ...

for RSA based on the repertory grid. The algorithm incorporates user relevance judgments as a means to deal with the inherent problems associated with the specification of semantic attributes. The algorithm is implemented and tested on the human face image database and the initial results are encouraging. In essence, we have developed an overall methodology/test bed to facilitate experimentatio...