Partha Pratim Roy, Umapada Pal, & Josep Llados. (2009). Seal detection and recognition: An approach for document indexing. In 10th International Conference on Document Analysis and Recognition (101–105).
Abstract: Reliable indexing of documents having seal instances can be achieved by recognizing seal information. This paper presents a novel approach for detecting and classifying such multi-oriented seals in these documents. First, Hough Transform based methods are applied to extract the seal regions in documents. Next, isolated text characters within these regions are detected. Rotation and size invariant features and a support vector machine based classifier have been used to recognize these detected text characters. Next, for each pair of character, we encode their relative spatial organization using their distance and angular position with respect to the centre of the seal, and enter this code into a hash table. Given an input seal, we recognize the individual text characters and compute the code for pair-wise character based on the relative spatial organization. The code obtained from the input seal helps to retrieve model hypothesis from the hash table. The seal model to which we get maximum hypothesis is selected for the recognition of the input seal. The methodology is tested to index seal in rotation and size invariant environment and we obtained encouraging results.
|
Partha Pratim Roy, Umapada Pal, Josep Llados, & Mathieu Nicolas Delalandre. (2009). Multi-Oriented and Multi-Sized Touching Character Segmentation using Dynamic Programming. In 10th International Conference on Document Analysis and Recognition (11–15).
Abstract: In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region at the background portion. Using Convex Hull information, we use these background information to find some initial points to segment a touching string into possible primitive segments (a primitive segment consists of a single character or a part of a character). Next these primitive segments are merged to get optimum segmentation and dynamic programming is applied using total likelihood of characters as the objective function. SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment, we obtained encouraging results.
|
|
Partha Pratim Roy, Umapada Pal, Josep Llados, & F. Kimura. (2008). Convex Hull based Approach for Multi-oriented Character Recognition form Graphical Documents. In 19th International Conference on Pattern Recognition.
|
|
Partha Pratim Roy, Umapada Pal, & Josep Llados. (2008). Recognition of Multi-oriented Touching Characters in Graphical Documents. In Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, (Vol. 16, 297–304).
|
|
Partha Pratim Roy, Umapada Pal, & Josep Llados. (2008). Multi-oriented English Text Line Extraction using Background and Foreground Information. In Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, (315–322).
|
|
Partha Pratim Roy, Umapada Pal, & Josep Llados. (2008). Morphology Based Handwritten Line Segmentation using Foreground and Background Information. In International Conference on Frontiers in Handwriting Recognition, (241–246).
|
Marçal Rusiñol, Farshad Nourbakhsh, Dimosthenis Karatzas, Ernest Valveny, & Josep Llados. (2010). Perceptual Image Retrieval by Adding Color Information to the Shape Context Descriptor. In 20th International Conference on Pattern Recognition (1594–1597).
Abstract: In this paper we present a method for the retrieval of images in terms of perceptual similarity. Local color information is added to the shape context descriptor in order to obtain an object description integrating both shape and color as visual cues. We use a color naming algorithm in order to represent the color information from a perceptual point of view. The proposed method has been tested in two different applications, an object retrieval scenario based on color sketch queries and a color trademark retrieval problem. Experimental results show that the addition of the color information significantly outperforms the sole use of the shape context descriptor.
|
Marçal Rusiñol, Josep Llados, & Gemma Sanchez. (2010). Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings. PAA - Pattern Analysis and Applications, 13(3), 321–331.
Abstract: In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes.
|
|
Partha Pratim Roy, Josep Llados, & Umapada Pal. (2009). A Complete System for Detection and Recognition of Text in Graphical Documents using Background Information. In 5th International Conference on Computer Vision Theory and Applications.
|
|
Partha Pratim Roy, & Josep Llados. (2008). Multi-Oriented Character Recognition from Graphical Documents. In 2nd International Conference on Cognition and Recognition (30–35).
|
|
Partha Pratim Roy, Josep Llados, & Umapada Pal. (2007). Text/Graphics Separation in Color Maps. In International Conference on Computing: Theory and Applications (545–551).
|
|
Marçal Rusiñol, Josep Llados, & Philippe Dosch. (2007). Camera-Based Graphical Symbol Detection. In 9th IEEE International Conference on Document Analysis and Recognition (Vol. 2, 884–888).
|
|
Marçal Rusiñol, Philippe Dosch, & Josep Llados. (2007). Boundary Shape Recognition Using Accumulated Length and Angle Information. In 3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:210–217.
|
Marçal Rusiñol, K. Bertet, Jean-Marc Ogier, & Josep Llados. (2009). Symbol Recognition Using a Concept Lattice of Graphical Patterns. In 8th IAPR International Workshop on Graphics Recognition.
Abstract: In this paper we propose a new approach to recognize symbols by the use of a concept lattice. We propose to build a concept lattice in terms of graphical patterns. Each model symbol is decomposed in a set of composing graphical patterns taken as primitives. Each one of these primitives is described by boundary moment invariants. The obtained concept lattice relates which symbolic patterns compose a given graphical symbol. A Hasse diagram is derived from the context and is used to recognize symbols affected by noise. We present some preliminary results over a variation of the dataset of symbols from the GREC 2005 symbol recognition contest.
|
Marçal Rusiñol, Agnes Borras, & Josep Llados. (2010). Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images. PRL - Pattern Recognition Letters, 31(3), 188–201.
Abstract: This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results.
Keywords: Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings
|
