11 research outputs found
On the use of metrics for multi-dimensional descriptors clustering
The Visual Thesaurus is a new query approach when no starting image is available. It is a concise representation of all similar regions in a panel of visual patches; the user arranges the visual patches according to his mental target image. The construction of the Visual Thesaurus needs a reliable region description and a clustering algorithm that reflects the variety of the database. In this paper, we develop a new region description schema based on Harris color points of interest. We also evaluate the relevance of several multi-dimensional matching metrics when measuring the similarity between regions described by variable signature dimensions. We outline the need of clustering to speed up the computation process as well. Moreover, we adopted the relational clustering algorithm to categorize regions according to Harris points of interest features. Generated clusters are represented by prototypes that compose the âpage zero â of the Visual Thesaurus. We tested our approach on generic database, the relevance of obtained clusters is evaluated subjectively. Index Terms â Image region analysis, Pattern matching, Image texture analysis, Image classification, Pattern clusterin
Recherche par thésaurus visuel et composition spatiale dans les bases d'images
Les systĂšmes usuels proposent Ă l'utilisateur de sĂ©lectionner une image ou une rĂ©gion requĂȘte soit tirĂ©e de la base soit issue d'une collection externe. Nous nous sommes penchĂ©s sur le cas oĂč l'exemple n'existe pas ou n'est pas appropriĂ© Ă l'image mentale que se fait l'utilisateur d'une cible donnĂ©e. Le paradigme du ThĂ©saurus Visuel permet de gĂ©nĂ©rer des catĂ©gories de rĂ©gions segmentĂ©es dont les reprĂ©sentants sont proposĂ©s comme une page zĂ©ro Ă l'utilisateur pour composer sa requĂȘte mentale en sĂ©lectionnant les patchs visuels Ă sa guise. Nous nous sommes intĂ©ressĂ©s dans ce travail Ă la gĂ©nĂ©ration des rĂ©sumĂ©s visuels des bases d'images selon la complexitĂ© des rĂ©gions et suivant les schĂ©mas de descriptions associĂ©s. La segmentation grossiĂšre des images gĂ©nĂšre des composantes visuelles dont la description par des attributs photomĂ©triques globaux tels que des distributions de couleurs quantifiĂ©es ne permet pas d'englober toute l'information photomĂ©trique sous-jacente. Les descripteurs locaux extraits autour des points d'intĂ©rĂȘt de Harris complĂštent le schĂ©ma de description global et infĂšrent une robustesse Ă la catĂ©gorisation des rĂ©gions. Cette derniĂšre fait appel Ă des algorithmes de compĂ©tition agglomĂ©rative et d'autres relationnels couplĂ©s Ă des mesures de similaritĂ© non-traditionnelles pour obtenir des catĂ©gories de rĂ©gions visuellement et structurellement cohĂ©rentes. Cette nouvelle approche est exploitĂ©e pour la composition logique et spatiale des patchs pour satisfaire la requĂȘte mentale de l'utilisateur. Les items de la page zĂ©ro sont les reprĂ©sentants des catĂ©gories de rĂ©gions dont l'orientation spatiale relative est dĂ©crite au moyen d'un histogramme angulaire pondĂ©rĂ© qui s'adapte Ă la rĂ©gularitĂ© et Ă la distribution des pixels dans la rĂ©gion. Les requĂȘtes se dĂ©composent en une partie logique et une autre spatiale dont les rĂ©sultats sont retournĂ©s en utilisant des tables d'associations et des intersections d'histogrammes respectivement.The choice of the starting example is an important issue for content-based image retrieval approaches. Usual systems suggest to the user to look for images similar to the one he selected either among the database itself or from an external image collection; the results are retrieved according to specific metrics suitable with extracted descriptors. In this work, we investigated the case of a missing or at least inappropriate starting example and hence the need of mental image composition in order to initiate the search process. To do so, the paradigm of Visual Thesaurus stands for a visual summary of all regions of the database, these segmented regions are clustered into coherent categories from which we select the representatives to compose the initial "page zero". Our interest was oriented toward the construction of a reliable visual thesaurus that meets the requirements of coarse segmentation and wide variability in region's photometric and structural complexity. Global attributes are suitable to likely homogenous regions whereas fine local descriptors through Harris points of interest infer robustness and visual coherence to the categorization step. The clustering requires, on the one hand, fuzzy agglomerative algorithms but also, in case of textured patterns, relational dual formulation depending mainly on the dimension of the description space. The objective of our work is to provide an alternative to starting example by composing the mental query through the arrangement of the visual patches selected from the Visual Thesaurus. Pairs of regions are described by a weighted angular spatial histogram to determine the orientation between an argument region and a referent one. Accordingly, both logical and spatial compositions are involved; returned results rely on inverted files indexation and histogram intersection metrics respectively.ORSAY-PARIS 11-BU Sciences (914712101) / SudocSudocFranceF
www-rocq.inria.fr/imedia/Muscle/WP5 Contents
2.1 Local descriptors for content-based image retrieval......... 6 2.1.1 Point of interest detection..................