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Author |
Agnes Borras; Josep Llados |
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Title |
Similarity-Based Object Retrieval Using Appearance and Geometric Feature Combination |
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Book Chapter |
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Year |
2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:113–120 |
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LNCS |
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4478 |
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33–39 |
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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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Girona (Spain) |
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978-3-540-72848-1 |
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DAG @ dag @ BoL2007a; IAM @ iam @ BoL2007a |
Serial |
776 |
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Author |
Agnes Borras |
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Title |
Contributions to the Content-Based Image Retrieval Using Pictorial Queries |
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Book Whole |
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Year |
2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The broad access to digital cameras, personal computers and Internet, has lead to the generation of large volumes of data in digital form. If we want an effective usage of this huge amount of data, we need automatic tools to allow the retrieval of relevant information. Image data is a particular type of information that requires specific techniques of description and indexing. The computer vision field that studies these kind of techniques is called Content-Based Image Retrieval (CBIR). Instead of using text-based descriptions, a system of CBIR deals on properties that are inherent in the images themselves. Hence, the feature-based description provides a universal via of image expression in contrast with the more than 6000 languages spoken in the world.
Nowadays, the CBIR is a dynamic focus of research that has derived in important applications for many professional groups. The potential fields of application can be such diverse as: the medical domain, the crime prevention, the protection of the intel- lectual property, the journalism, the graphic design, the web search, the preservation of cultural heritage, etc.
The definition on the role of the user is a key point in the development of a CBIR application. The user is in charge to formulate the queries from which the images are retrieved. We have centered our attention on the image retrieval techniques that use queries based on pictorial information. We have identified a taxonomy composed by four main query paradigms: query-by-selection, query-by-iconic-composition, query- by-sketch and query-by-paint. Each one of these paradigms allows a different degree of user expressivity. From a simple image selection, to a complete painting of the query, the user takes control of the input in the CBIR system.
Along the chapters of this thesis we have analyzed the influence that each query paradigm imposes in the internal operations of a CBIR system. Moreover, we have proposed a set of contributions that we have exemplified in the context of a final application. |
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Address |
Barcelona (Spain) |
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Thesis |
Ph.D. thesis |
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Publisher |
Ediciones Graficas Rey |
Place of Publication |
Bellaterra |
Editor |
Josep Llados |
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DAG; |
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DAG @ dag @ Bor2009; IAM @ iam @ Bor2009 |
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1269 |
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Author |
Jon Almazan; Ernest Valveny; Alicia Fornes |
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Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
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Conference Article |
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Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
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6669 |
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1-8 |
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This paper presents a new model for the description and recognition of distorted shapes, where the image is represented by a pixel density distribution based on the Blurred Shape Model combined with a non-linear image deformation model. This leads to an adaptive structure able to capture elastic deformations in shapes. This method has been evaluated using thee different datasets where deformations are present, showing the robustness and good performance of the new model. Moreover, we show that incorporating deformation and flexibility, the new model outperforms the BSM approach when classifying shapes with high variability of appearance. |
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Las Palmas de Gran Canaria. Spain |
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Springer-Verlag |
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Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
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IbPRIA |
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DAG; |
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Admin @ si @ AVF2011 |
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1732 |
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Author |
Arnau Baro |
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Title |
Reading Music Systems: From Deep Optical Music Recognition to Contextual Methods |
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Book Whole |
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Year |
2022 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The transcription of sheet music into some machine-readable format can be carried out manually. However, the complexity of music notation inevitably leads to burdensome software for music score editing, which makes the whole process
very time-consuming and prone to errors. Consequently, automatic transcription
systems for musical documents represent interesting tools.
Document analysis is the subject that deals with the extraction and processing
of documents through image and pattern recognition. It is a branch of computer
vision. Taking music scores as source, the field devoted to address this task is
known as Optical Music Recognition (OMR). Typically, an OMR system takes an
image of a music score and automatically extracts its content into some symbolic
structure such as MEI or MusicXML.
In this dissertation, we have investigated different methods for recognizing a
single staff section (e.g. scores for violin, flute, etc.), much in the same way as most text recognition research focuses on recognizing words appearing in a given line image. These methods are based in two different methodologies. On the one hand, we present two methods based on Recurrent Neural Networks, in particular, the
Long Short-Term Memory Neural Network. On the other hand, a method based on Sequence to Sequence models is detailed.
Music context is needed to improve the OMR results, just like language models
and dictionaries help in handwriting recognition. For example, syntactical rules
and grammars could be easily defined to cope with the ambiguities in the rhythm.
In music theory, for example, the time signature defines the amount of beats per
bar unit. Thus, in the second part of this dissertation, different methodologies
have been investigated to improve the OMR recognition. We have explored three
different methods: (a) a graphic tree-structure representation, Dendrograms, that
joins, at each level, its primitives following a set of rules, (b) the incorporation of Language Models to model the probability of a sequence of tokens, and (c) graph neural networks to analyze the music scores to avoid meaningless relationships between music primitives.
Finally, to train all these methodologies, and given the method-specificity of
the datasets in the literature, we have created four different music datasets. Two of them are synthetic with a modern or old handwritten appearance, whereas the
other two are real handwritten scores, being one of them modern and the other
old. |
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Thesis |
Ph.D. thesis |
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Publisher |
IMPRIMA |
Place of Publication |
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Editor |
Alicia Fornes |
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978-84-124793-8-6 |
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DAG; |
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no |
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Call Number |
Admin @ si @ Bar2022 |
Serial |
3754 |
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Author |
Ayan Banerjee; Palaiahnakote Shivakumara; Parikshit Acharya; Umapada Pal; Josep Llados |
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Title |
TWD: A New Deep E2E Model for Text Watermark Detection in Video Images |
Type |
Conference Article |
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Year |
2022 |
Publication |
26th International Conference on Pattern Recognition |
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Deep learning; U-Net; FCENet; Scene text detection; Video text detection; Watermark text detection |
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Abstract |
Text watermark detection in video images is challenging because text watermark characteristics are different from caption and scene texts in the video images. Developing a successful model for detecting text watermark, caption, and scene texts is an open challenge. This study aims at developing a new Deep End-to-End model for Text Watermark Detection (TWD), caption and scene text in video images. To standardize non-uniform contrast, quality, and resolution, we explore the U-Net3+ model for enhancing poor quality text without affecting high-quality text. Similarly, to address the challenges of arbitrary orientation, text shapes and complex background, we explore Stacked Hourglass Encoded Fourier Contour Embedding Network (SFCENet) by feeding the output of the U-Net3+ model as input. Furthermore, the proposed work integrates enhancement and detection models as an end-to-end model for detecting multi-type text in video images. To validate the proposed model, we create our own dataset (named TW-866), which provides video images containing text watermark, caption (subtitles), as well as scene text. The proposed model is also evaluated on standard natural scene text detection datasets, namely, ICDAR 2019 MLT, CTW1500, Total-Text, and DAST1500. The results show that the proposed method outperforms the existing methods. This is the first work on text watermark detection in video images to the best of our knowledge |
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Montreal; Quebec; Canada; August 2022 |
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ICPR |
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DAG; |
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Call Number |
Admin @ si @ BSA2022 |
Serial |
3788 |
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Author |
Josep Llados; J. Lopez-Krahe; Enric Marti |
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Title |
A Hough-based method for hatched pattern detection in maps and diagrams. |
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Miscellaneous |
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Year |
1999 |
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Proceedings of the International Conference on Document Analysis and Recognition. |
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Bangalore-India |
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DAG @ dag @ LlM1999b |
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1 |
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Author |
Josep Llados; Gemma Sanchez; Enric Marti |
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Title |
A String-Based Method to Recognize Symbols and Structural Textures in Architectural Plans. |
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Miscellaneous |
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1997 |
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Second IAPR Workshop on Graphics Recognition, pp. 287–294. |
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DAG @ dag @ LSM1997 |
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44 |
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Author |
V. Chapaprieta; Ernest Valveny |
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Title |
Handwritten Digit Recognition Using Point Distribution Models. |
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Miscellaneous |
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2001 |
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Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, 1:49–54. |
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DAG @ dag @ ChV2001 |
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83 |
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Author |
Josep Llados |
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Title |
Interpretacio de dibuixos linials fets a ma alçada mitjançant isomorfisme entre subgrafs i transformacio de Hough |
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Report |
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1996 |
Publication |
CVC Technical Report #10 |
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CVC (UAB) |
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DAG @ dag @ Lla1996 |
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85 |
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Author |
Gemma Sanchez; Josep Llados |
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Title |
A Graph Grammar to Recognize Textured Symbols. |
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2001 |
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Sixth International Conference on Document Analysis and Recognition, ICDAR 2001, 465–469. |
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USA |
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DAG @ dag @ SLl2001 |
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