Search results for "image retrieval"
showing 10 items of 69 documents
A Semantic Collaborative Clustering Approach Based on Confusion Matrix
2019
In this paper we discuss about a new images retrieval technique based on clustering. We argue that images don’t have an intrinsic meaning, but they can receive different interpretation. These images can complicate documents retrieval. However, users need a quick and direct access to documents. To answer this requirement, we propose a retrieval approach which use a collaborative clustering technique based on Confusion matrix.
Novel Indexing Method of Relations Between Salient Objects
2011
Since the last decade, images have been integrated into several application domains such as GIS, medicine, etc. This integration necessitates new managing methods particularly in image retrieval. Queries should be formulated using different types of features such as low-level features of images (histograms, color distribution, etc.), spatial and temporal relations between salient objects, semantic features, etc. In this chapter, we propose a novel method for identifying and indexing several types of relations between salient objects. Spatial relations are used here to show how our method can provide high expressive power to relations in comparison to the traditional methods.
Searching Silk Fabrics by Images Leveraging on Knowledge Graph and Domain Expert Rules
2021
The production of European silk textile is an endangered intangible cultural heritage. Digital tools can nowadays be developed to help preserving it, or even to make it more accessible for the public and the fashion industry. In this paper, we propose an image-based retrieval tool that leverages on a knowledge graph describing the silk textile production as well as rules formulated by experts of this domain. Out of several possible similarity scenarios, two have proven to work best and have been integrated into an exploratory search engine.
The Anatomy of an Optical Biopsy Semantic Retrieval System
2012
A case-based computer-aided diagnosis system assists physicians and other medical personnel in the interpretation of optical biopsies obtained through confocal laser endomicroscopy. Extraction in CLE images shows promising results on inferring semantic metadata from low-level features. In order to effectively ensure the interoperability with potential third-party applications, the system provides an interface compliant with the recent standards ISO/IEC 15938-12:2008 (MPEG Query Format) and ISO/IEC 24800 (JPEG Search).
A hybrid multi-objective optimization algorithm for content based image retrieval
2013
Abstract Relevance feedback methods in CBIR (Content Based Image Retrieval) iteratively use relevance information from the user to search the space for other relevant samples. As several regions of interest may be scattered through the space, an effective search algorithm should balance the exploration of the space to find new potential regions of interest and the exploitation of areas around samples which are known relevant. However, many algorithms concentrate the search on areas which are close to the images that the user has marked as relevant, according to a distance function in the (possibly deformed) multidimensional feature space. This maximizes the number of relevant images retriev…
Unsupervised Clustering in Personal Photo Collections
2008
In this paper we propose a probabilistic approach for the automatic organization of collected pictures aiming at more effective representation in personal photo albums. Images are analyzed and described in two representation spaces, namely, faces and background. Faces are automatically detected, rectified and represented projecting the face itself in a common low dimensional eigenspace. Backgrounds are represented with low-level visual features based on RGB histogram and Gabor filter energy. Face and background information of each image in the collection is automatically organized by mean-shift clustering technique. Given the particular domain of personal photo libraries, where most of the …
Integrating user preference to similarity queries over medical images datasets
2010
International audience; Large amounts of images from medical exams are being stored in databases, so developing retrieval techniques is an important research problem. Retrieval based on the image visual content is usually better than using textual descriptions, as they seldom gives every nuances that the user may be interested in. Content-based image retrieval employs the similarity among images for retrieval. However, similarity is evaluated using numeric methods, and they often orders the images by similarity in a way rather distinct from the user's intention. In this paper, we propose a technique to allow expressing the user's preference over attributes associated to the images, so simil…
Multimedia Retrieval in a Medical Image Collection: Results Using Modality Classes
2013
The effective communication between user and systems is one main aim in the Multimedia Information Retrieval field. In this paper the modality classification of images is used to expand the user queries within the ImageCLEF Medical Retrieval collection provided by organizers. Our main contribution is to show how and when results can be improved by understanding modality-related challenges. To do so, a detailed analysis of the results of the experiments carried out is presented and the comparison between these results shows that the improvement using modality class query expansion is query-dependent.
A statistical model for magnitudes and angles of wavelet frame coefficients and its application to texture retrieval
2014
Abstract This paper presents a texture descriptor based on wavelet frame transforms. At each position in the image, and for each resolution level, we consider both vertical and horizontal wavelet detail coefficients as the components of a bivariate random vector. The magnitudes and angles of these vectors are computed. At each level the empirical histogram of magnitudes is modeled by a Generalized Gamma distribution, and the empirical histogram of angles is modeled by a different version of the von Mises distribution that accounts for histograms with 2 modes. Each texture is characterized by few parameters. A new distance is presented (based on the Kullback–Leibler divergence) that allows g…
Trademarks recognition based on local regions similarities
2010
This paper deals with content based image retrieval. We propose a logo recognition algorithm based on local regions, where the trademark (or logo) image is segmented by the clustering of points of interest obtained by Harris corners detector. The minimum rectangle surrounding each cluster is detected forming the regions of interest. Global features such as Hu moments and histograms of each local region are combined to find similar logos in the database. Similarity is measured based on the integrated minimum average distance of the individual components. The results obtained demonstrate tolerance to logos distortions such as rotation, occlusion and noise.