0000000000131747
AUTHOR
Esther De Ves
A New Wavelet-Based Texture Descriptor for Image Retrieval
This paper presents a novel texture descriptor based on the wavelet transform. First, we will consider vertical and horizontal coefficients at the same position as the components of a bivariate random vector. The magnitud and angle of these vectors are computed and its histograms are analyzed. This empirical magnitud histogram is modelled by using a gamma distribution (pdf). As a result, the feature extraction step consists of estimating the gamma parameters using the maxima likelihood estimator and computing the circular histograms of angles. The similarity measurement step is done by means of the well-known Kullback-Leibler divergence. Finally, retrieval experiments are done using the Bro…
A relevance feedback CBIR algorithm based on fuzzy sets
CBIR (content-based image retrieval) systems attempt to allow users to perform searches in large picture repositories. In most existing CBIR systems, images are represented by vectors of low level features. Searches in these systems are usually based on distance measurements defined in terms of weighted combinations of the low level features. This paper presents a novel approach to combining features when using multi-image queries consisting of positive and negative selections. A fuzzy set is defined so that the degree of membership of each image in the repository to this fuzzy set is related to the user's interest in that image. Positive and negative selections are then used to determine t…
A statistical model for magnitudes and angles of wavelet frame coefficients and its application to texture retrieval
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…
Feature extraction and correlation for time-to-impact segmentation using log-polar images
In this article we present a technique that allows high-speed movement analysis using the accurate displacement measurement given by the feature extraction and correlation method. Specially, we demonstrate that it is possible to use the time to impact computation for object segmentation. This segmentation allows the detection of objects at different distances.
Resuming Shapes with Applications
Many image processing tasks need some kind of average of different shapes. Frequently, different shapes obtained from several images have to be summarized. If these shapes can be considered as different realizations of a given random compact set, then the natural summaries are the different mean sets proposed in the literature. In this paper, new mean sets are defined by using the basic transformations of Mathematical Morphology (dilation, erosion, opening and closing). These new definitions can be considered, under some additional assumptions, as particular cases of the distance average of Baddeley and Molchanov. The use of the former and new mean sets as summary descriptors of shapes is i…
Game-based learning supported by audience response tools: game proposals and preliminary assessment
The so-called game-based learning strategies are based on introducing games in the classrooms to improve aspects such as student performance, concentration and effort. Currently, they provide a very useful resource to increase the motivation of university students, generating a better atmosphere among peers and between student and teacher, which in turn is generally translated into better academic results. However, the design of games that successfully achieve the desired teaching-learning objectives is not a trivial task. This work focuses on the design of games that allow the assessment of ICT-related university subjects. Specifically, three different games are proposed, all based on stud…
A novel dynamic multi-model relevance feedback procedure for content-based image retrieval
This paper deals with the problem of image retrieval in large databases with a big semantic gap by a relevance feedback procedure. We present a novel algorithm for modelling the users's preferences in the content-based image retrieval system.The proposed algorithm considers the probability of an image belonging to the set of those sought by the user, and estimates the parameters of several local logistic regression models whose inputs are the low-level image features. A Principal Component Analysis method is applied to the original vector to reduce its high dimensionality. The relevance probabilities predicted by these local models are combined by means of a weighted average. These weights …
FCA-based knowledge representation and local generalized linear models to address relevance and diversity in diverse social images
Abstract In social image retrieval, the main goal is to offer a relevant but also diverse result set of images to the user. To address relevance and diversity at the same time, we propose a multi-modal procedure. This approach deals with the diversification problem using a two-step procedure based on the application of Formal Concept Analysis (FCA) to organize the text content of the images, followed by a Hierarchical Agglomerative Clustering (HAC) step to find the topics addressed by the images. FCA detects the latent concepts covered by the images in the result set, organizing them according to these concepts. In the second step, clustering is carried out to group together the ones with a…
Multimedia Retrieval by Means of Merge of Results from Textual and Content Based Retrieval Subsystems
The main goal of this paper it is to present our experiments in ImageCLEF 2009 Campaign (photo retrieval task). In 2008 we proved empirically that the Text-based Image Retrieval (TBIR) methods defeats the Content-based Image Retrieval CBIR "quality" of results, so this time we developed several experiments in which the CBIR helps the TBIR. The TBIR System [6] main improvement is the named-entity sub-module. In case of the CBIR system [3] the number of low-level features has been increased from the 68 component used at ImageCLEF 2008 up to 114 components, and only the Mahalanobis distance has been used. We propose an ad-hoc management of the topics delivered, and the generation of XML struct…
Girls4STEM: Gender Diversity in STEM for a Sustainable Future
Science, Technology, Engineering, and Mathematics (STEM) are key disciplines towards tackling the challenges related to the Sustainable Development Goals. However, evidence shows that women are enrolling in these disciplines in a smaller percentage than men, especially in Engineering related fields. As stated by the United Nations Women section, increasing the number of women studying and working in STEM fields is fundamental towards achieving better solutions to the global challenges, since the potential for innovation is larger. In this paper, we present the Girls4STEM project, which started in 2019 at the Escola Tè
IOWA Operators and Its Application to Image Retrieval
This paper presents a relevance feedback procedure based on logistic regression analysis. Since, the dimension of the feature vector associated to each image is typically larger than the number of evaluated images by the user, different logistic regression models have to be fitted separately. Each fitted model provides us with a relevance probability and a confidence interval for that probability. In order to aggregate these set of probabilities and confidence intervals we use an IOWA operator. The results will show the success of our algorithm and that OWA operators are an efficient and natural way of dealing with this kind of fusion problems.
Intelligent eye
This paper describes Intelligent Eye, a mobile phone interactive leisure guide that offers location-based multimedia information. The information offered is related to the user's position, so the main goal of this work is the development of an efficient system to detect where the user is pointing his/her camera at by means of a content-based image retrieval algorithm (CBIR). The CBIR procedure uses color histograms in the HS color space extracted from images, and employs Kullback-Leibler divergence as the similarity measure. Intelligent Eye can be used in a wide range of camera-equipped mobile phones; however, efficiency is improved if GPS data is available. In order to outperform other sys…
Modeling user preferences in content-based image retrieval: A novel attempt to bridge the semantic gap
This paper is concerned with content-based image retrieval from a stochastic point of view. The semantic gap problem is addressed in two ways. First, a dimensional reduction is applied using the (pre-calculated) distances among images. The dimension of the reduced vector is the number of preferences that we allow the user to choose from, in this case, three levels. Second, the conditional probability distribution of the random user preference, given this reduced feature vector, is modeled using a proportional odds model. A new model is fitted at each iteration. The score used to rank the image database is based on the estimated probability function of the random preference. Additionally, so…