The need for efficient content-based image retrieval system has increased hugely. Efficient and effective retrieval techniques of images are desired because of the explosive growth of digital images. Content based image retrieval (CBIR) is a promising approach because of its automatic indexing retrieval based on their semantic features and visual appearance. In this proposed system we investiga...

One of the content based image retrieval techniques is the shape based technique which allows users to ask for objects similar in shape to a query object. We propose a novel method for shape representation and similarity measure which we call the grid based method and evaluate its performance by comparing it with two popular methods, namely, the Fourier descriptors method and the moment invaria...

Content-based image retrieval has become one of the most active research areas in the past few years. In this paper various methodologies used in the research area of Content Based Image Retrieval techniques using Relevance Feedback are discussed. The comparison and analysis of these methods is done. Relevance feedback techniques were incorporated into Content-based image retrieval for obtainin...

This paper presents an image retrieval method based on keyblocks combing with interest points, furthermore the generation of codebook is also utilized to enhance the retrieval performance, where the balance between the retrieved precision and time cost can decide the codebook size of this CBIR system. Finally, the proposed method is compared with the method that only depends on interest points ...

We present image spot queries as an alternative for content-based image retrieval. Through image spots (i.e., selective parts of images) users can better indicate which parts of the image are relevant for their query. Compared to traditional approaches, we allow users to search image databases for local image (spatial, color and color transition) characteristics rather than global features.

This paper proposes an effective and efficient approach to content-based image retrieval by integrating global visual features and fuzzy region-based color and texture features. The Cauchy function is utilized to fuzzify each independent regional color and texture feature for addressing the issues associated with the color/texture inaccuracies and segmentation uncertainties. The overall similar...

Content-based image retrieval (CBIR) makes use of image features, such as color and texture, to index images with minimal human intervention. Content-based image retrieval can be used to locate medical images in large databases. This chapter introduces a content-based approach to medical image retrieval. Fundamentals of the key components of content-based image retrieval systems are introduced ...

Article history: Received 16 November 2007 Received in revised form 4 May 2008 Accepted 23 June 2008

We propose a novel query-dependent feature aggregation (QDFA) method for medical image retrieval. The QDFA method can learn an optimal feature aggregation function for a multi-example query, which takes into account multiple features and multiple examples with different importance. The experiments demonstrate that the QDFA method outperforms three other feature aggregation methods. key words: C...

This paper provides an overview of current research in image information retrieval and provides an outline of areas for future research. The approach is broad and interdisciplinary and focuses on three aspects of image research (IR): text-based retrieval, content-based retrieval, and user interactions with image information retrieval systems. The review concludes with a call for image retrieval...