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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Morphology Based Handwritten Line Segmentation using Foreground and Background Information |
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Conference Article |
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2008 |
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International Conference on Frontiers in Handwriting Recognition, |
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241–246 |
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Montreal (Canada) |
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ICFHR |
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DAG @ dag @ RPL2008a |
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1050 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Recognition of Multi-oriented Touching Characters in Graphical Documents |
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Conference Article |
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2008 |
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Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, |
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16 |
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297–304 |
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ICVGIP ’08 |
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DAG @ dag @ RPL2008c |
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1080 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Seal detection and recognition: An approach for document indexing |
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Conference Article |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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101–105 |
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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. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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ICDAR |
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DAG @ dag @ RPL2009b |
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1239 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
![goto web page url](img/www.gif)
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Title |
Seal Object Detection in Document Images using GHT of Local Component Shapes |
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Conference Article |
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2010 |
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10th ACM Symposium On Applied Computing |
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23–27 |
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Due to noise, overlapped text/signature and multi-oriented nature, seal (stamp) object detection involves a difficult challenge. This paper deals with automatic detection of seal from documents with cluttered background. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors (distance and angular position) computed from recognition result of individual connected components (characters). Recognition of multi-scale and multi-oriented component is done using Support Vector Machine classifier. Generalized Hough Transform (GHT) is used to detect the seal and a voting is casted for finding possible location of the seal object in a document based on these spatial feature descriptor of components pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal object in a document. Experimental results show that, the method is efficient to locate seal instance of arbitrary shape and orientation in documents. |
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Sierre, Switzerland |
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SAC |
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DAG @ dag @ RPL2010a |
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1291 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Query Driven Word Retrieval in Graphical Documents |
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Conference Article |
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2010 |
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9th IAPR International Workshop on Document Analysis Systems |
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191–198 |
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In this paper, we present an approach towards the retrieval of words from graphical document images. In graphical documents, due to presence of multi-oriented characters in non-structured layout, word indexing is a challenging task. The proposed approach uses recognition results of individual components to form character pairs with the neighboring components. An indexing scheme is designed to store the spatial description of components and to access them efficiently. Given a query text word (ascii/unicode format), the character pairs present in it are searched in the document. Next the retrieved character pairs are linked sequentially to form character string. Dynamic programming is applied to find different instances of query words. A string edit distance is used here to match the query word as the objective function. Recognition of multi-scale and multi-oriented character component is done using Support Vector Machine classifier. To consider multi-oriented character strings the features used in the SVM are invariant to character orientation. Experimental results show that the method is efficient to locate a query word from multi-oriented text in graphical documents. |
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Boston; USA |
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978-1-60558-773-8 |
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DAS |
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DAG |
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DAG @ dag @ RPL2010b |
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1433 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Touching Text Character Localization in Graphical Documents using SIFT |
Type |
Conference Article |
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2009 |
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In proceedings 8th IAPR International Workshop on Graphics Recognition |
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Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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La rochelle; July 2009 |
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GREC |
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DAG @ dag @ RPL2009c |
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1445 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Document Seal Detection Using Ght and Character Proximity Graphs |
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Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition |
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PR |
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44 |
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6 |
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1282-1295 |
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Seal recognition; Graphical symbol spotting; Generalized Hough transform; Multi-oriented character recognition |
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This paper deals with automatic detection of seal (stamp) from documents with cluttered background. Seal detection involves a difficult challenge due to its multi-oriented nature, arbitrary shape, overlapping of its part with signature, noise, etc. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors computed from recognition result of individual connected components (characters). Scale and rotation invariant features are used in a Support Vector Machine (SVM) classifier to recognize multi-scale and multi-oriented text characters. The concept of generalized Hough transform (GHT) is used to detect the seal and a voting scheme is designed for finding possible location of the seal in a document based on the spatial feature descriptor of neighboring component pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal in a document. Experiment is performed in an archive of historical documents of handwritten/printed English text. Experimental results show that the method is robust in locating seal instances of arbitrary shape and orientation in documents, and also efficient in indexing a collection of documents for retrieval purposes. |
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Elsevier |
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Admin @ si @ RPL2011 |
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1820 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Text line extraction in graphical documents using background and foreground |
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Journal Article |
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2012 |
Publication |
International Journal on Document Analysis and Recognition |
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IJDAR |
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15 |
Issue |
3 |
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227-241 |
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0,405 JCR
In graphical documents (e.g., maps, engineering drawings), artistic documents etc., the text lines are annotated in multiple orientations or curvilinear way to illustrate different locations or symbols. For the optical character recognition of such documents, individual text lines from the documents need to be extracted. In this paper, we propose a novel method to segment such text lines and the method is based on the foreground and background information of the text components. To effectively utilize the background information, a water reservoir concept is used here. In the proposed scheme, at first, individual components are detected and grouped into character clusters in a hierarchical way using size and positional information. Next, the clusters are extended in two extreme sides to determine potential candidate regions. Finally, with the help of these candidate regions,
individual lines are extracted. The experimental results are presented on different datasets of graphical documents, camera-based warped documents, noisy images containing seals, etc. The results demonstrate that our approach is robust and invariant to size and orientation of the text lines present in
the document. |
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1433-2833 |
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Admin @ si @ RPL2012b |
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2134 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Touching Text Character Localization in Graphical Documents using SIFT |
Type |
Book Chapter |
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2010 |
Publication |
Graphics Recognition. Achievements, Challenges, and Evolution. 8th International Workshop, GREC 2009. Selected Papers |
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6020 |
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199-211 |
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Support Vector Machine; Text Component; Graphical Line; Document Image; Scale Invariant Feature Transform |
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Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-13727-3 |
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Admin @ si @ RPL2010c |
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2408 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados; F. Kimura |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Convex Hull based Approach for Multi-oriented Character Recognition form Graphical Documents |
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Conference Article |
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2008 |
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19th International Conference on Pattern Recognition |
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Tampa (Florida) |
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ICPR |
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DAG @ dag @ RPL2008d |
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1073 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre |
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Multi-Oriented and Multi-Sized Touching Character Segmentation using Dynamic Programming |
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Conference Article |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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11–15 |
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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. |
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Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ RPL2009a |
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1240 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre |
![download PDF file pdf](img/file_PDF.gif)
![goto web page (via DOI) doi](img/doi.gif)
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Title |
Multi-oriented touching text character segmentation in graphical documents using dynamic programming |
Type |
Journal Article |
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2012 |
Publication |
Pattern Recognition |
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PR |
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45 |
Issue |
5 |
Pages |
1972-1983 |
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2,292 JCR
The touching character segmentation problem becomes complex when touching strings are multi-oriented. Moreover in graphical documents sometimes characters in a single-touching string have different orientations. Segmentation of such complex touching is more challenging. 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 in the background portion. Based on the convex hull information, at first, we use this background information to find some initial points for segmentation of a touching string into possible primitives (a primitive consists of a single character or part of a character). Next, the primitives are merged to get optimum segmentation. A dynamic programming algorithm is applied for this purpose using the total likelihood of characters as the objective function. A 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. Experiments were performed in different databases of real and synthetic touching characters and the results show that the method is efficient in segmenting touching characters of arbitrary orientations and sizes. |
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0031-3203 |
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Admin @ si @ RPL2012a |
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2133 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Patricia Marquez |
![download PDF file pdf](img/file_PDF.gif)
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Title |
Conditions Ensuring Accuracy of Local Optical Flow Schemes |
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Report |
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2010 |
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CVC Tehcnical Report |
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157 |
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Accurate computation of optical flow is a key-point in many image processing fields. Detection of anomalous and unpredicted agents (such as pedestrians, bikers or cars) in urban scenes or pathology discrimination in medical imaging sequences, to mention just a two. The above kinds sequences present two main difficulties for standard optical flow techniques. On one hand, variability in acquisition conditions (illuminance, medical imaging modality, ...) force an alterantive representation for images fulfilling the britghtness constancy constrain. On the hand, current variational schemes produce oversmoothed fields unable to properly model discontinuous behaviours such as collisions or functionless pathological areas. This master project explores the abilities and limitations of local and global optical flow approaches. The master student will put especial emphasis in the theoretical grounds behind in order to design a variational framework combining the theoretical advantages of the considered techniques. In particular an optical flow based on Gabor phase tracking (developed in the group for medical imaging) will be generalized to urban scenes. |
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Bellaterra 08193, Barcelona, Spain |
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IAM @ iam @ Mar2010 |
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1582 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Patricia Marquez |
![find book details (via ISBN) isbn](img/isbn.gif)
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Title |
A Confidence Framework for the Assessment of Optical Flow Performance |
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2015 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Optical Flow (OF) is the input of a wide range of decision support systems such as car driver assistance, UAV guiding or medical diagnose. In these real situations, the absence of ground truth forces to assess OF quality using quantities computed from either sequences or the computed optical flow itself. These quantities are generally known as Confidence Measures, CM. Even if we have a proper confidence measure we still need a way to evaluate its ability to discard pixels with an OF prone to have a large error. Current approaches only provide a descriptive evaluation of the CM performance but such approaches are not capable to fairly compare different confidence measures and optical flow algorithms. Thus, it is of prime importance to define a framework and a general road map for the evaluation of optical flow performance.
This thesis provides a framework able to decide which pairs “ optical flow – confidence measure” (OF-CM) are best suited for optical flow error bounding given a confidence level determined by a decision support system. To design this framework we cover the following points:
Descriptive scores. As a first step, we summarize and analyze the sources of inaccuracies in the output of optical flow algorithms. Second, we present several descriptive plots that visually assess CM capabilities for OF error bounding. In addition to the descriptive plots, given a plot representing OF-CM capabilities to bound the error, we provide a numeric score that categorizes the plot according to its decreasing profile, that is, a score assessing CM performance.
Statistical framework. We provide a comparison framework that assesses the best suited OF-CM pair for error bounding that uses a two stage cascade process. First of all we assess the predictive value of the confidence measures by means of a descriptive plot. Then, for a sample of descriptive plots computed over training frames, we obtain a generic curve that will be used for sequences with no ground truth. As a second step, we evaluate the obtained general curve and its capabilities to really reflect the predictive value of a confidence measure using the variability across train frames by means of ANOVA.
The presented framework has shown its potential in the application on clinical decision support systems. In particular, we have analyzed the impact of the different image artifacts such as noise and decay to the output of optical flow in a cardiac diagnose system and we have improved the navigation inside the bronchial tree on bronchoscopy. |
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July 2015 |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Debora Gil;Aura Hernandez |
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978-84-943427-2-1 |
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IAM; 600.075 |
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Admin @ si @ Mar2015 |
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2687 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Patricia Marquez; Debora Gil ; Aura Hernandez-Sabate |
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Title |
Error Analysis for Lucas-Kanade Based Schemes |
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Conference Article |
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2012 |
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9th International Conference on Image Analysis and Recognition |
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7324 |
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184-191 |
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Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance |
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Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures. |
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Aveiro, Portugal |
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Springer-Verlag Berlin Heidelberg |
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english |
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Campilho, Aurélio and Kamel, Mohamed |
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Lecture Notes in Computer Science |
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LNCS |
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0302-9743 |
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978-3-642-31294-6 |
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ICIAR |
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IAM |
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IAM @ iam @ MGH2012a |
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1899 |
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