|
Records |
Links |
|
Author |
Ernest Valveny; Enric Marti |


|
|
Title |
Learning of structural descriptions of graphic symbols using deformable template matching |
Type |
Conference Article |
|
Year |
2001 |
Publication |
Proc. Sixth Int Document Analysis and Recognition Conf |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
455-459 |
|
|
Keywords  |
|
|
|
Abstract |
Accurate symbol recognition in graphic documents needs an accurate representation of the symbols to be recognized. If structural approaches are used for recognition, symbols have to be described in terms of their shape, using structural relationships among extracted features. Unlike statistical pattern recognition, in structural methods, symbols are usually manually defined from expertise knowledge, and not automatically infered from sample images. In this work we explain one approach to learn from examples a representative structural description of a symbol, thus providing better information about shape variability. The description of a symbol is based on a probabilistic model. It consists of a set of lines described by the mean and the variance of line parameters, respectively providing information about the model of the symbol, and its shape variability. The representation of each image in the sample set as a set of lines is achieved using deformable template matching. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;IAM; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VMA2001 |
Serial |
1654 |
|
Permanent link to this record |
|
|
|
|
Author |
Ernest Valveny; Enric Marti |


|
|
Title |
Deformable Template Matching within a Bayesian Framework for Hand-Written Graphic Symbol Recognition |
Type |
Journal Article |
|
Year |
2000 |
Publication |
Graphics Recognition Recent Advances |
Abbreviated Journal |
|
|
|
Volume |
1941 |
Issue |
|
Pages |
193-208 |
|
|
Keywords  |
|
|
|
Abstract |
We describe a method for hand-drawn symbol recognition based on deformable template matching able to handle uncertainty and imprecision inherent to hand-drawing. Symbols are represented as a set of straight lines and their deformations as geometric transformations of these lines. Matching, however, is done over the original binary image to avoid loss of information during line detection. It is defined as an energy minimization problem, using a Bayesian framework which allows to combine fidelity to ideal shape of the symbol and flexibility to modify the symbol in order to get the best fit to the binary input image. Prior to matching, we find the best global transformation of the symbol to start the recognition process, based on the distance between symbol lines and image lines. We have applied this method to the recognition of dimensions and symbols in architectural floor plans and we show its flexibility to recognize distorted symbols. |
|
|
Address |
|
|
|
Corporate Author |
Springer Verlag |
Thesis |
|
|
|
Publisher |
Springer Verlag |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;IAM; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ MVA2000 |
Serial |
1655 |
|
Permanent link to this record |
|
|
|
|
Author |
Ernest Valveny; Enric Marti |


|
|
Title |
Hand-drawn symbol recognition in graphic documents using deformable template matching and a Bayesian framework |
Type |
Conference Article |
|
Year |
2000 |
Publication |
Proc. 15th Int Pattern Recognition Conf |
Abbreviated Journal |
|
|
|
Volume |
2 |
Issue |
|
Pages |
239-242 |
|
|
Keywords  |
|
|
|
Abstract |
Hand-drawn symbols can take many different and distorted shapes from their ideal representation. Then, very flexible methods are needed to be able to handle unconstrained drawings. We propose here to extend our previous work in hand-drawn symbol recognition based on a Bayesian framework and deformable template matching. This approach gets flexibility enough to fit distorted shapes in the drawing while keeping fidelity to the ideal shape of the symbol. In this work, we define the similarity measure between an image and a symbol based on the distance from every pixel in the image to the lines in the symbol. Matching is carried out using an implementation of the EM algorithm. Thus, we can improve recognition rates and computation time with respect to our previous formulation based on a simulated annealing algorithm. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
0-7695-0750-6 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;IAM; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VAM2000 |
Serial |
1656 |
|
Permanent link to this record |
|
|
|
|
Author |
Ernest Valveny; Enric Marti |


|
|
Title |
Application of deformable template matching to symbol recognition in hand-written architectural draw |
Type |
Conference Article |
|
Year |
1999 |
Publication |
Proceedings of the Fifth International Conference on |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords  |
|
|
|
Abstract |
We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
Bangalore (India) |
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;IAM; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VAM1999a |
Serial |
1657 |
|
Permanent link to this record |
|
|
|
|
Author |
Ernest Valveny; Enric Marti |

|
|
Title |
Recognition of lineal symbols in hand-written drawings using deformable template matching |
Type |
Conference Article |
|
Year |
1999 |
Publication |
Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
|
|
|
Keywords  |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;IAM; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VAM1999 |
Serial |
1658 |
|
Permanent link to this record |
|
|
|
|
Author |
Ernest Valveny; Enric Marti |

|
|
Title |
Dimensions analysis in hand-drawn architectural drawings |
Type |
Conference Article |
|
Year |
1997 |
Publication |
(SNRFAI’97) 7th Spanish National Symposium on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
90-91 |
|
|
Keywords  |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
CVC-UAB |
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;IAM; |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VAM1997 |
Serial |
1659 |
|
Permanent link to this record |
|
|
|
|
Author |
Ernest Valveny; Ricardo Toledo; Ramon Baldrich; Enric Marti |

|
|
Title |
Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching |
Type |
Conference Article |
|
Year |
2002 |
Publication |
Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages |
502–507 |
|
|
Keywords  |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG;RV;CAT;IAM;CIC;ADAS |
Approved |
no |
|
|
Call Number |
IAM @ iam @ VTB2002 |
Serial |
1660 |
|
Permanent link to this record |
|
|
|
|
Author |
Lluis Pere de las Heras; Ahmed Sheraz; Marcus Liwicki; Ernest Valveny; Gemma Sanchez |


|
|
Title |
Statistical Segmentation and Structural Recognition for Floor Plan Interpretation |
Type |
Journal Article |
|
Year |
2014 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
|
|
Volume |
17 |
Issue |
3 |
Pages |
221-237 |
|
|
Keywords  |
|
|
|
Abstract |
A generic method for floor plan analysis and interpretation is presented in this article. The method, which is mainly inspired by the way engineers draw and interpret floor plans, applies two recognition steps in a bottom-up manner. First, basic building blocks, i.e., walls, doors, and windows are detected using a statistical patch-based segmentation approach. Second, a graph is generated, and structural pattern recognition techniques are applied to further locate the main entities, i.e., rooms of the building. The proposed approach is able to analyze any type of floor plan regardless of the notation used. We have evaluated our method on different publicly available datasets of real architectural floor plans with different notations. The overall detection and recognition accuracy is about 95 %, which is significantly better than any other state-of-the-art method. Our approach is generic enough such that it could be easily adopted to the recognition and interpretation of any other printed machine-generated structured documents. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer Berlin Heidelberg |
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1433-2833 |
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; ADAS; 600.076; 600.077 |
Approved |
no |
|
|
Call Number |
HSL2014 |
Serial |
2370 |
|
Permanent link to this record |
|
|
|
|
Author |
Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal |

|
|
Title |
A Novel Mutual Nearest Neighbor based Symmetry for Text Frame Classification in Video |
Type |
Journal Article |
|
Year |
2011 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
|
Volume |
44 |
Issue |
8 |
Pages |
1671-1683 |
|
|
Keywords  |
|
|
|
Abstract |
In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection, etc. We propose a new text frame classification method that introduces a combination of wavelet and median moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max–Min clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called mutual nearest neighbor based symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created data show that the proposed method gives promising results in terms of recall and precision at the block and frame levels. Further, we also show how existing text detection methods tend to misclassify non-text frames as text frames in term of recall and precision at both the block and frame levels. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ SDP2011 |
Serial |
1727 |
|
Permanent link to this record |
|
|
|
|
Author |
Jon Almazan; Ernest Valveny; Alicia Fornes |

|
|
Title |
Deforming the Blurred Shape Model for Shape Description and Recognition |
Type |
Conference Article |
|
Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
|
|
Volume |
6669 |
Issue |
|
Pages |
1-8 |
|
|
Keywords  |
|
|
|
Abstract |
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. |
|
|
Address |
Las Palmas de Gran Canaria. Spain |
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
Springer-Verlag |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
IbPRIA |
|
|
Notes |
DAG; |
Approved |
no |
|
|
Call Number |
Admin @ si @ AVF2011 |
Serial |
1732 |
|
Permanent link to this record |