This paper provides a formal speciication for concept-based image retrieval using triples. To eeectively manage a vast amount of images, we may need an image retrieval systems capable of indexing and searching images based on the characteristics of their content. However, such a content-based image retrieval technique alone may not satisfy user queries if retrieved images turn out to be relevan...

In our paper, we deal with the challenge of extending automatically the classic image indexing by visual relationship features. The visual relationship features are discovered automatically from images. They contribute to make more efficient the content-based indexing. More particularly, we develop an advanced content-based indexing articulated around the following notions : classic indexing, c...

Content based image retrieval (CBIR) concerns the retrieval of similar images from image databases, using feature vectors extracted from images. These feature vectors globally define the visual content present in an image, defined by e.g., texture, colour, shape, and spatial relations between vectors. Herein, we propose the definition of feature vectors using the Local Binary Pattern (LBP) oper...

The performance of an indexing technique, namely, a system of feature extraction and similarity measure, is strongly related to the test bed in content-based image retrieval. A theoretical framework is proposed for image database modeling. The goal is to investigate the relationship between a given indexing technique and a given image database. As an analogy to the concept of perplexity of a te...

Since the relative proportion of multimedia (video, image and audio) data within databases is expected to increase substantially in the future, keyword-based indexing would be inadequate and eecient content-based query and retrieval are required. The problem of devising content-based query, indexing, and retrieval for these newer data types remains an open and challenging problem. While conside...

Content-based image retrieval has attained a position of overwhelming dominance in computer vision with the advent of digital cameras and explosion of images in the Internet and Clouds. Finding the most relevant images in a short time is a challenging job with many big cloud sites competing in image search in terms of accuracy and recall. This paper addresses an image retrieval system employing...

A new approach to indexing in model-based vision is introduced; using indexing features whose deformed instances are present in a number of different object models. Hypotheses are generated by matching an indexing feature with an image using a viewing transformation incorporating the deformation; the parameter values of the deformational component provide specific indices to those models relate...

This paper introduces a new method to analyse the image texture and to index the image database. We present a new strategy to reduce the computational time to extract image features with high retrieval accuracy. We also propose a method to reduce the image feature dimension, so any robust indexing methods can be used. By weighting the extracted image features, a system may perceive the image co...

Inter-subject analysis of anatomical and functional brain imaging data requires the images to be registered to a common coordinate system in which anatomical features are aligned. Intensity-based volume registration methods can align subcortical structures well, but the variability in sulcal folding patterns typically results in misalignment of the cortical surface. Conversely, surface-based re...

Due to increasing the usage of media, the utilization of video play central role as it supports various applications. Video is the particular media which contains complex collection of objects like audio, motion, text, color and picture. Due to the rapid growth of this information video indexing process is mandatory for fast and effective retrieval. Many current indexing techniques fails to ext...