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Sergio Vera, Debora Gil, Agnes Borras, F. Javier Sanchez, Frederic Perez, Marius G. Linguraru, et al. (2012). "Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs " In H. Yoshida et al (Ed.), Workshop on Computational and Clinical Applications in Abdominal Imaging (Vol. 7029, 223–230). Lecture Notes in Computer Science. Berlin: Springer Link.
Abstract: Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations.
Keywords: medial manifolds, abdomen.
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Francesc Tous, Agnes Borras, Robert Benavente, Ramon Baldrich, Maria Vanrell, & Josep Llados. (2002). "Textual Descriptors for browsing people by visual appearence. " In 5è. Congrés Català d’Intel·ligència Artificial CCIA.
Abstract: This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building.
Keywords: Image retrieval, textual descriptors, colour naming, colour normalization, graph matching.
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Francesc Tous, Agnes Borras, Robert Benavente, Ramon Baldrich, Maria Vanrell, & Josep Llados. (2002)." Textual Descriptions for Browsing People by Visual Apperance." In Lecture Notes in Artificial Intelligence (Vol. 2504, pp. 419–429). Springer Verlag.
Abstract: This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building
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Agnes Borras. (2002)." High-Level Clothes Description Based on Colour-Texture Features." .
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Agnes Borras, Francesc Tous, Josep Llados, & Maria Vanrell. (2003). "High-Level Clothes Description Based on Color-Texture and Structural Features " In Lecture Notes in Computer Science (Vol. 2652, 108–116).
Abstract: This work is a part of a surveillance system where content- based image retrieval is done in terms of people appearance. Given an image of a person, our work provides an automatic description of his clothing according to the colour, texture and structural composition of its garments. We present a two-stage process composed by image segmentation and a region-based interpretation. We segment an image by modelling it due to an attributed graph and applying a hybrid method that follows a split-and-merge strategy. We propose the interpretation of five cloth combinations that are modelled in a graph structure in terms of region features. The interpretation is viewed as a graph matching with an associated cost between the segmentation and the cloth models. Fi- nally, we have tested the process with a ground-truth of one hundred images.
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Agnes Borras, Francesc Tous, Josep Llados, & Maria Vanrell. (2003). "High-Level Clothes Description Based on Colour-Texture and Structural Features " In 1rst. Iberian Conference on Pattern Recognition and Image Analysis IbPRIA 2003.
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Agnes Borras, & Josep Llados. (2005). "Object Image Retrieval by Shape Content in Complex Scenes Using Geometric Constraints " In Pattern Recognition And Image Analysis (Vol. 3522, 325–332). Springer Link.
Abstract: This paper presents an image retrieval system based on 2D shape information. Query shape objects and database images are repre- sented by polygonal approximations of their contours. Afterwards they are encoded, using geometric features, in terms of predefined structures. Shapes are then located in database images by a voting procedure on the spatial domain. Then an alignment matching provides a probability value to rank de database image in the retrieval result. The method al- lows to detect a query object in database images even when they contain complex scenes. Also the shape matching tolerates partial occlusions and affine transformations as translation, rotation or scaling.
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Anton Cervantes, Gemma Sanchez, Josep Llados, Agnes Borras, & A. Rodriguez. (2005)." Biometric Recognition Based on Line Shape Descriptors" In Sixth IAPR International Workshop on Graphics Recognition (GREC 2005) (335–344).
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Anton Cervantes, Gemma Sanchez, Josep Llados, Agnes Borras, & Ana Rodriguez. (2006). "Biometric Recognition Based on Line Shape Descriptors " In Lecture Notes in Computer Science (Vol. 3926, 346–357,). Springer Link.
Abstract: Abstract. In this paper we propose biometric descriptors inspired by shape signatures traditionally used in graphics recognition approaches. In particular several methods based on line shape descriptors used to iden- tify newborns from the biometric information of the ears are developed. The process steps are the following: image acquisition, ear segmentation, ear normalization, feature extraction and identification. Several shape signatures are defined from contour images. These are formulated in terms of zoning and contour crossings descriptors. Experimental results are presented to demonstrate the effectiveness of the used techniques.
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Agnes Borras, & Josep Llados. (2007). "Similarity-Based Object Retrieval Using Appearance and Geometric Feature Combination " In 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:113–120 (Vol. 4478, 33–39).
Abstract: This work presents a content-based image retrieval system of general purpose that deals with cluttered scenes containing a given query object. The system is flexible enough to handle with a single image of an object despite its rotation, translation and scale variations. The image content is divided in parts that are described with a combination of features based on geometrical and color properties. The idea behind the feature combination is to benefit from a fuzzy similarity computation that provides robustness and tolerance to the retrieval process. The features can be independently computed and the image parts can be easily indexed by using a table structure on every feature value. Finally a process inspired in the alignment strategies is used to check the coherence of the object parts found in a scene. Our work presents a system of easy implementation that uses an open set of features and can suit a wide variety of applications.
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